ICCSS 2019 2019 International Conference on Information,
Cybernetics, and Computational Social Systems
September 27-29, 2019
Chongqing, China
CONFERENCE DIGEST
Organizers:
Southwest University Chongqing Three Gorges University Chongqing Jiaotong University
Sponsors:
IEEE Systems, Man and
Cybernetics Society
IFAC Technical Committee on Economic,
Business, and Financial Systems (TC 9.1)
Conference Digest 2019 International Conference on
Information, Cybernetics, and Computational Social Systems
IEEE ICCSS 2019 September 27-29, 2019
Chongqing, China Organized by
Southwest University, Chongqing, China Chongqing Three Gorges University, Chongqing, China Chongqing Jiaotong University, Chongqing, China
Technically cosponsored by IEEE Systems, Man and Cybernetics Society IEEE SMCA Technical Committee on Computational Psychophysiology IFAC Technical Committee on Economic, Business, and Financial Systems (TC 9.1)
Foreword On behalf of the Organizing Committee, we sincerely welcome you to join us at the 2019 International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS 2019) being held in Chongqing, China, during September 27-29, 2019. ICCSS 2019 aims to provide an international forum that brings together those actively involved in computational social systems, cybernetics, and information processing, to report on up-to-the-minute innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances in all aspects of social systems, computation, cybernetics, and information processing.
ICCSS 2019 attracted a total of 85 submissions involving the most advanced development and research coverage with computational social systems, social computing, social networks analysis and web mining, data mining and machine learning, data analytics and data visualization, cybernetics and systems science, the intelligent systems, collective intelligence, computational intelligence, position and location supported intelligence, signal and image processing, wavelets, multiresolution and information processing, information security, pattern recognition and computer vision, robotic systems, service systems and organizations, smart sensor networks, system modeling and control, technology assessment, etc. According to the strict peer review of planning committee members and reviewers, 55 papers (acceptance rate 64%) were selected and included in the conference proceedings.
Many organizations and volunteers made great contributions toward the success of this conference. We would like to express our sincere gratitude to IEEE Systems, Man and Cybernetics Society, and IFAC Technical Committee on Economic, Business, and Financial Systems (TC 9.1) for their sponsorship, Southwest University, Chongqing Three Gorges University and Chongqing Jiaotong University for their Organization. We would also like to sincerely thank all the committee members for their great efforts in organizing the conference. Special thanks to all technical committee members and reviewers for their professional review to ensure the high quality of the meeting process. Finally, we would like to thank all speakers, authors, and participants for their great contributions and supports to make ICCSS 2019 a success. We sincerely hope that all participants can gain academic achievements, enhance mutual communication, broaden their horizons and gain friendship in this conference!
Program Chairs
Prof. Chuandong Li Prof. Xing He Prof. Huaqing Li Prof. Zhengguang Wu
Location: Haiyu Hotspring Hotel, Shuangyuan Road 198, Beibei District, Chongqing, China
Welcome Message
Welcome to the 2019 International Conference on Information, Cybernetics, and Computational Social
Systems (ICCSS 2019)!
ICCSS 2019 provides an international forum that brings together those actively involved in
computational social systems, cybernetics, and information processing, to report on up-to-the-minute
innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances
in all aspects of social systems, computation, cybernetics, and information processing.
We would like to take this opportunity to thank the Technical Program Committee comprising of many
Area Chairs and Reviewers from all over the world, who have worked diligently to ensure that high
quality papers will be presented and published in the proceedings. We also acknowledge the support of
and express our sincere appreciation to the members of the local organizing committee. We are also
grateful to the advice and guidance of the Executive Committee of the Southwest University, China and
the IEEE SMC Society (SMCS). Lastly and most importantly, we thank all of you, the authors and
delegates, for participating in ICCSS 2019, sharing your knowledge and experience and contributing to
the advancement of science and technology for the improvement of the quality of our lives.
We wish each and every one a most pleasant experience at ICCSS 2019 in Chongqing.
C. L. Philip Chen Chuandong Li General Chair, ICCSS 2019 Program Chair, ICCSS 2019
IEEE ICCSS 2019 Conference Digest
Table of Contents
Committees …………………………………...…..…………………………………1
Program at a Glance…………….….……………….…………………………...…...3
Plenary Speeches…………………………….…………….…………………….......4
Oral Sessions……………………….…………………………...………………..…..10
Paper Abstracts…………………………….…………….…………….…................16
Keynotes …………………………..….…………….……………………..................25
Conference Registration ..……………..…………………..………………...…….....34
General Information ..…………………..……………..………………....…………...35
Index of Authors ………………………………. …………………...………..………42
1
Committees
Honorary General Chairs
Tianyou Chai, Northeastern University, China Jie Chen, Tongji University, China
General Chair C. L. Philip Chen, South China University of Technology, China
General Co-Chairs
Gang Feng, City University of Hong Kong, Hong Kong, China Xiaofeng Liao, Chongqing University, China Tingwen Huang, Texas A&M University at Qatar, Qatar Wei Zhang, Chongqing Three Gorges University, China
Program Chair Chuandong Li, Southwest University, China
Program Co-Chairs Xing He, Southwest University, China Huaqing Li, Southwest University, China Zhengguang Wu, Zhejiang University, China
Organizing Committee Chairs
Tieshan Li, Dalian Maritime University, China Junzhi Yu, Beijing University, China Shaojiang Deng, Chongqing University, China
Organizing Committee Co-Chairs
Yanjun Liu, Liaoning University of Technology, China Qinglei Hu, Beihang University, China Honggui Han, Beijing University of Technology, China
Award Committee Chairs
Jian Sun, Beijing Institute of Technology, China Wenwu Yu, Southeast University, China Hongyi Li, Bohai University, China
Award Committee Co-Chairs
Long Cheng, Chinese Academy of Sciences, China Qiankun Song, Chongqing Jiaotong University, China
Poster Session Chairs Lidan Wang, Southwest University, China Shiyuan Wang, Southwest University, China Yuming Feng, Chongqing Three Gorges University, China
Publicity Chairs Lorenzo Marconi, University of Bologna, Italy Choon Ki Ahn, Korea University, South Korea Haitao Zhang, Huazhong University of Science and Technology, China
2
Publicity Co-Chairs James Lam, The University of Hong Kong, Hong Kong, China Yajun Pan, Dalhousie University, Canada Mohammed Chadli, University of Picardie Jules Verne, France
Special Session Chairs
Xiaodi Li, Shandong Normal University, China Tao Xiang, Chongqing University, China Huiwei Wang, Southwest University, China
Local Arrangement Chairs
Xin Wang, Southwest University, China Yiyuan Xie, Southwest University, China Jiang Xiong,Chongqing Three Gorges University, China Bo Gao, Southwest University, China
Registration Chair Tong Zhang, South China University of Technology, China
Publication Chairs Long Chen, University of Macau, Macau, China Tong Zhang, South China University of Technology, China Ling Chen, Southwest University, China
Secretaries Zhengran Cao, Southwest University, China Zhilong He, Southwest University, China
3
Program at a Glance
Sept. 27-29, 2019 Chongqing, China
September 27 (Friday)
13:00-22:00 On-site Registration Haiyu Hotspring Hotel (海宇温泉大酒店)
18:00-21:00 Dinner 2F Shisheng Room (2 楼食生居)
September 28 (Saturday)
08:30-09:00 Opening Ceremony 3F Guohui Hall (3 楼国会厅)
09:00-12:00 Plenary Speeches
12:00-14:00 Lunch 1F Western Restaurant (1 楼西餐厅)
14:00-18:00 Oral Session I* 3F Runyu Hall (3 楼润宇厅)
14:00-18:00 Oral Session II* 3F Keyu Hall (3 楼科宇厅)
14:00-18:00 Oral Session III* 2F VIP Hall (2 楼贵宾厅)
18:00-20:00 Dinner 1F Golden Chinese Hall (1 楼金色大厅)
20:00-20:30 Awards Ceremony 1F Golden Chinese Hall (1 楼金色大厅)
September 29 (Sunday)
08:30-12:00 Keynotes 3F Guohui Hall (3 楼国会厅)
12:00-14:00 Lunch 2F VIP Hall (2 楼贵宾厅)
14:00-18:00 Keynotes 3F Guohui Hall (3 楼国会厅)
*15 minutes (Speech: 12 minutes, Q&A: 3 minutes) are scheduled for oral presentation including discussions for each paper.
4
Plenary Speech I
Title: Artificial Intelligence and Intelligent Industries: A New IT and
Big 5G Perspective
Prof. Fei-Yue Wang
Chinese Academy of Sciences (CAS), Beijing, China
Abstract: With the rapid development of artificial intelligence, the intelligent industries have also made great progress. This report will explain the development of artificial intelligence from the perspective of New IT and Big 5G. Clearly, the integration of New IT (Intelligent Technology) and Big 5G (Grids 5.0) will bring tremendous changes for the future smart society.
Fei-Yue Wang received his Ph.D. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990. He joined the University of Arizona in 1990 and became a Professor and Director of the Robotics and Automation Lab (RAL) and Program in Advanced Research for Complex Systems (PARCS). In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Overseas Chinese
Talents Program from the State Planning Council and “100 Talent Program” from CAS, and in 2002, was appointed as the Director of the Key Lab of Complex Systems and Intelligence Science, CAS. From 2006 to 2010, he was Vice President for Research, Education, and Academic Exchanges at the Institute of Automation, CAS. In 2011, he became the State Specially Appointed Expert and the Director of the State Key Laboratory for Management and Control of Complex Systems.
Dr. Wang’s current research focuses on methods and applications for parallel systems, social computing, parallel intelligence and knowledge automation. He was the Founding Editor-in-Chief of the International Journal of Intelligent Control and Systems (1995-2000), Founding EiC of IEEE ITS Magazine (2006-2007), EiC of IEEE Intelligent Systems (2009-2012), and EiC of IEEE Transactions on ITS (2009-2016). Currently he is EiC of IEEE Transactions on Computational Social Systems, Founding EiC of IEEE/CAA Journal of Automatica Sinica, and Chinese Journal of Command and Control. Since 1997, he has served as General or Program Chair of more than 20 IEEE, INFORMS, ACM, and ASME conferences. He was the President of IEEE ITS Society (2005-2007), Chinese Association for Science and Technology (CAST, USA) in 2005, the American Zhu Kezhen Education Foundation (2007-2008), the Vice President of the ACM China Council (2010-2011), and the
5
Vice President and Secretary General of Chinese Association of Automation (CAA, 2008-2018). Since 2019, he has been the President of CAA Supervision Council. Dr. Wang has been elected as Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and was awarded the Outstanding Scientist by ACM for his research contributions in intelligent control and social computing. He received IEEE ITS Outstanding Application and Research Awards in 2009, 2011 and 2015, and IEEE SMC Norbert Wiener Award in 2014.
6
Plenary Speech II
Title: Adaptive Event-Triggered Control of Multi-Agent Systems
Prof. Gang Feng
City University of Hong Kong, Hong Kong, China
Abstract: In this talk event-triggered control will be first overviewed. The motivation and major event-triggering mechanisms will be discussed. The challenging issue on exclusion of Zeno behavior will be highlighted. Then the adaptive event-triggered control will be considered for heterogeneous multi-agent systems. A fully distributed adaptive even-triggered control scheme will be presented for output consensus of such multi-agent systems. It is shown that the output consensus problem can be solved by the proposed adaptive event-triggered control scheme if a necessary and sufficient condition is satisfied. The feasibility of the proposed control scheme is discussed by excluding Zeno behavior. A numerical example is given to illustrate the effectiveness of the proposed control scheme.
Gang Feng received the B.Eng and M.Eng. Degrees in Automatic Control from Nanjing Aeronautical Institute, China in 1982 and in 1984 respectively, and the Ph.D. degree in Electrical Engineering from the University of Melbourne, Australia in 1992.
Professor Feng was a Lecturer in Royal Melbourne Institute of Technology, 1991 and a Senior Lecturer/Lecturer, University of New South Wales, 1992-1999. He has been with City
University of Hong Kong since 2000 where he is now a Chair Professor of Mechatronic Engineering. He has received a ChangJiang Chair Professorship award conferred by Ministry of Education, the Alexander von Humboldt Fellowship, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the Shimemura Young Author Prize of the Asian Control Conference, the Best Paper Award of IEEE International Conference on Neural Networks and Signal Processing, and the Best Theoretical Paper Award in the Second World Congress on Intelligent Control and Automation. He is listed as a SCI highly cited researcher by Clarivate Analytics. He is an author of one research approach, and over 300 SCI indexed papers including over 130 in IEEE Transactions. His research interests include intelligent systems and control, networked control systems, and multi-agent systems and control.
Professor Feng is a Fellow of IEEE. He has been the Associate Editor of IEEE Transactions Automatic Control, IEEE Transactions on Fuzzy Systems, IEEE Transactions Systems, Man, and Cybernetics, Mechatronics, Journal of Systems Science and Complexity, and Journal of Control Theory and Applications.
7
Plenary Speech III
Title：Control Theory of the Cooperative Control of
Multi-Autonomous Systems and Its Application
Prof. Renquan Lu
Guangdong University of Technology, Guangdong, China
Abstract: Introduction of the cooperative control under leader failure, event-triggered, and variable topology.
Professor Renquan Lu works on the intelligent decision and cooperative control. In this field, he has publicated more than 140 papers including the 27 high-cited papers, 3 books and almost 20 patents. He received the first prize of nature science award and the second prize of science and technology progress award of Ministry of Education of China. Professor Lu is also honored as Distinguished Professor of Pearl River Scholars Program of Guangdong Province, the Distinguished Professor of Yangtze River Scholars Program by the Ministry of
Education of China. He was supported by the National Science Fund for Distinguished Young Scientists of China and dericts Innovation Teams in Priority Areas and Innovative Talents Trainning Base accredited by the Ministry of Science and Technology of China, the Key Laboratory of Guangdong Province. Besides the theory development, Professor Lu also focuses on the engineering application, the cooperative control method for the autonomous systems has been successfully implemented in the container position robot and intelligent equipment of China International Marine Containters Ltd.
8
Plenary Speech IV
Title：Data Modelling and Analysis Using the New Discriminative
Broad Learning System
Prof. C. L. Philip Chen
South China University of Technology, Guangdong, China
Abstract: After a very fast and efficient discriminative Broad Learning System (BLS) that takes advantage of flatted structure and incremental learning has been developed, this talk will address data modeling with outliers and labeling errors. A robust broad learning system (RBLS) is derived by assuming the regression residual and output weights follow their respective distributions, where the output weights for robust modeling can be determined by maximum a posterior estimation. Furthermore, the robustness of RBLS can be enhanced by integrating the regularization theory. In addition, the framework of several BLS variants with their mathematical modellings will be given. The variations include cascade, recurrent, and broad-deep combination that cover existing deep-wide/broad-wide structures. From the experimental results, the BLS/RBLS and its variations outperforms several exist learning algorithms on regression performance over function approximation, time series prediction, face recognition, and data modelling.
C. L. Philip Chen is the Chair Professor and Dean of the College of Computer Science and Engineering, South China University of Technology. Being a Program Evaluator of the Accreditation Board of Engineering and Technology Education (ABET) in the U.S., for computer engineering, electrical engineering, and software engineering programs, he successfully architects the University of Macau’s Engineering and Computer Science programs receiving accreditations from Washington/Seoul Accord through Hong Kong Institute of
Engineers (HKIE), of which is considered as his utmost contribution in engineering/computer science education for Macau as the former Dean of the Faculty of Science and Technology. He is a Fellow of IEEE, AAAS, IAPR, CAA, and HKIE; a member of Academia Europaea (AE), European Academy of Sciences and Arts (EASA), and International Academy of Systems and Cybernetics Science (IASCYS). He received IEEE Norbert Wiener Award in 2018 for his contribution in systems and cybernetics, and machine learnings. He is also a 2018 highly cited researcher in Computer Science by Clarivate Analytics.
His current research interests include systems, cybernetics, and computational intelligence. Dr. Chen was a recipient of the 2016 Outstanding Electrical and
9
Computer Engineers Award from his alma mater, Purdue University, after he graduated from the University of Michigan at Ann Arbor, Ann Arbor, MI, USA in 1985. He was the IEEE Systems, Man, and Cybernetics Society President from 2012 to 2013, and currently, he is the Editor-in-Chief of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, and an Associate Editor of the IEEE Transactions on Fuzzy Systems, and IEEE Transactions on Cybernetics. He was the Chair of TC 9.1 Economic and Business Systems of International Federation of Automatic Control from 2015 to 2017 and currently is a Vice President of Chinese Association of Automation (CAA).
10
Oral Sessions Oral Session I
September 28, afternoon; 3F Runyu Hall (3 楼润宇厅)
Chair: Huaqing Li
Time Title Author
14:00 –
15:00
A New Approach to Stabilization of Delayed Markov Jump Systems via Event-Triggered
Control
Wenqian Xie and Yuping Zhang
Image Completion Method Considering Content and Sharpness Ruqi Wang and Qun Liu
H∞ Control for T-S Fuzzy Systems with Aperiodic Sampling
Jinnan Luo, Wenhong Tian, Shouming Zhong, Daixi Liao,
Jun Cheng and Kaibo Shi
Speaker Identification Based on PCC Feature Vector
Peichao He, Yi Zuo, Tieshan Li, C. L. Philip Chen, He Ma
and Junxia Liu
Impulsive Control with Time Windows for Hyperchaotic Exponential Synchronization
Hongjuan Wu, Xiang Hu, Yuming Feng and Zhengwen
Tu
15:00 –
16:00
Couple-Group Consensus for Cooperative-Competitive Heterogeneous Multi-Agent
Systems with Pinning Control Ting Gao and Lianghao Ji
A Fast Method of Function Approximation Using Broad Learning System
Yuzhuo Ma, Tieshan Li, Yi Zuo, C.L.Philip Chen, Liangen
Yuan and Qihe Shan An Adaptive Image Encryption Scheme
Based on Bit-Level Permutation Ping Wang and Jin Qiu
Adaptive Consensus Control of Nonlinear Fractional-Order Multi-Agent Systems with a
Leader Jiajun Yang
A Delay System Approach to Networked Control System via an Event-Triggered
Scheme Feng Hu and Xiaojie Su
16:00 –
16:30 Coffee break
16:30 –
17:30
Robust Convergence of Uncertain Fuzzy BAM Neural Networks with Time-Varying
Delays
Wei Zhang, Liangliang Li and Yuming Feng
An Evolutionary Model of For-Profit Enforcement and Pervasive Law-Violation
Kaiyue Wang, Tongkui Yu and Xu Jin
Differential Privacy Optimal Consensus for Multi-Agent System by Using Functional
Perturbation Xiangyu Bu and Tao Dong
Stabilization of Chen Chaotic System via Variable-Time Impulvise Control
Ruihan Liu, Hui Wang and Jiyang Chen
Intermittent Impulsive Consensus of Multi-Agent Systems
Kun Li, Tiantian Yu, Zhengle Zhang and Tiedong Ma
11
17:30 –
18:00
Double Closed-Loop Control Strategy for Electric Springs Based on PI Controller
Yun Zou, Shihao Xu and Michael Z. Q. Chen
Balanced Performance Preserving Model Reduction for Uncertain Semi-Markovian
Jump Systems: Continuous-Time Case
Huiyan Zhang, Wengang Ao, Shuai Yang and Peng Shi
Improving Prediction Accuracy of Protein Content in Corn by Using the
Multi-Population Genetic Algorithm and Partial Least Squares
Yongchao Wu and Guangyuan Liu
12
Oral Session II
September 28, afternoon; 3F Keyu Hall (3 楼科宇厅)
Chair: Xing He
Time Title Author
14:00 –
15:00
An Optimal Transmission Channel Selection Algorithm for Emergency Communication
Xidong Zhang, Heng Zhang, Wenhong Liu, Baojun Song,
Hongbo Zhang and Shujie Zhu Evolutionary Model of Braess’s Paradox and the Optimal Solution by Charging
Xianping Yu, Kaiyue Wang, Xin Wang and Tongkui Yu
A Kernel Recursive Mixed Error Criterion Algorithm for Chaotic Time Series
Prediction
Qishuai Wu, Yingsong Li, Wanlu Shi, Xinqi Huang and
Wei Xue Network Community Detection Using a
Backtracking-Based Discrete State Transition
Ke Yang, Xiaojun Zhou and Chaojie Li
Association Rules Hiding via Multi-Objective Differential Evolution Algorithm Nankun Mu and Fan Yang
15:00 –
16:00
Feature Space Oversampling Technique for Imbalanced Classification Haoyang Wang and He Huang
Stability Analysis on Variable-Time Impulsive Networks
Renyi Xie, Chuandong Li, Zhengran Cao and Zhilong He
Second-Order Wheeled Mobile Robot Based on Fractional-Order PD Controller
Xuchen Wang, Lu Liu, Yuxuan Huang, Qiuyue Wang, Pan Qi
and Gang Lu Input-to-State Stability of Impulsive Stochastic Nonlinear Systems with
Lyapunov Indefinite Derivative
Chenghui Mao, Chuandong Li and Wei Zhang
Global Exponential Stability of Memristive Complex-Valued Neural Networks with Mixed Time Delays and Impulse Effects
Xuejun Wang, Chuandong Li, Ling Chen and Jiyang Chen
16:00 –
16:30 Coffee break
16:30 –
17:30
Consensus Analysis Based on Saturated Impulsive Control in Networked
Multi-Agent Systems
Xinmiao Dong, Chuandong Li and Hui Wang
Couple-Group Consensus for Heterogeneous Multi-Agent Systems with Event-Triggered
Methods
Jianlei Xu, Shasha Yang, Qianzhu Wang and Lianghao Ji
Existence and Stability Analysis of Periodic Solution of FitzHugh-Nagumo Neuron Model with State-Dependent Impulse
Effects
Cong Liu, Hui Wang and Zhilong He
A Distributed Dynamic Resource Allocation Strategy in a Large-Scale Micro-Grids
Group Zao Fu and Xing He
A Recurrent Neural Network for Optimal Energy Management Considering the
Battery Cycle-Life in Smart Grid Miao Sun and Xing He
13
17:30 –
18:00
A Shrinkage Correntropy Based Algorithm Under Impulsive Noise Environment Wanlu Shi and Yingsong Li
Image Classification Based on Convolutional Neural Network and Support
Vector Machine Nankun Mu and Dewen Qiao
The Kernel Recursive Generalized Cauchy Kernel Loss Algorithm
Wei Shi, Kui Xiong and Shiyuan Wang
14
Oral Session III
September 28, afternoon; 2F VIP Hall (2 楼贵宾厅)
Chair: Huiwei Wang
Time Title Author
14:00 –
15:00
Robust Manhattan Non-Negative Matrix Factorization for Image Reconstruction
Xiangguang Dai, Wei Zhang and Yuming Feng
Expenential Synchronization of Memristive Cohen-Grossberg Neural Networks with Mixed
Time Delays
Yinghua Zhou, Jiamin Quan, Hongyi Liu and
Huiyu Nie
A Simple Motion Deblurring Method by Two Continuous Images
Jihai Zhang, Jianfeng Li, Guangyuan Liu, Tong
Chen, Tengteng Zhu and Bo Li
A Nonlinear Impulsive Control System with Impulse Time Windows and Un-Fixed
Coefficient of Impulsive Intensity
Yuming Feng, Xiaoyu Liu, Zitao Wang and Wei Zhang
Stability of Stochastic Systems with Variable-Time Impulses Jie Tan and Zhaohui Chen
15:00 –
16:00
Row-Stochastic Matrices Based Distributed Optimization Algorithm with Uncoordinated
Step-Sizes
Huaqing Li, Jinmeng Wang and Zheng Wang
Secure Consensus Control for Time-Varying Multi-Agent Systems with Mixed Types
Attacks
Xiaomeng Li, Wenbin Xiao, Qi Zhou and Hongyi Li
A Self-Learning Sliding Mode Controller for Biological Wastewater Treatment System
XiaolongWu, Honggui Han and Junfei Qiao
Raman Imaging Data Preprocessing for Quantitative Analysis Waihou Ao and Long Chen
A Multifunctional and Robust Learning Approach forHuman Motion Modelling
ChunyangZhang, Yongyi Xiao and Jiaqi Pu
16:00 –
16:30 Coffee break
16:30 –
17:30
Robust H∞ Control Based on Event-Triggered Optimization
Jiajie Lu, Yuan Fan and Teng Li
Rotating Consensus Control of Double-Integrator Multi-Agent Systems under
Directed Graphs Rui Ding and Wenfeng Hu
Planning PEV Fast-Charging Stations: A Data-Driven Distributionally Robust
Optimization Approach
Bo Zhou, Yuefei Yuan and Huiwei Wang
Integrated Pest Managements in a Pest-Natural Enemy System with Adaptation of Pest
Yi Yang, Changcheng Xiang and Shasha Yan
Lagrange Stability Analysis for Quaternion-Valued Memristive Neural Networks
Zhengwen Tu, Liangwei Wang, Tao Peng,
Liangliang Li and B.O. Onasanya
17:30 –
Error-Correcting Performance Comparison for Polar Codes, LDPC Codes and Convolutional
Chao Yang, Ming Zhan, Yi Deng, Meng Wang,
15
18:00 Codes in High-Performance Wireless Xiaohong Luo and Jie Zeng The Projective Synchronization of a HX-Type
Hyperchaotic Hyperjerk System Baojie Zhang
Annual Runoff Forecast Based on Cooperative Particle Swarm Projection Pursuit Regression
Model Xinxin Li and Jing Xu
16
Paper Abstracts
Saturday, September 28, 2019
Session SaO I: 14:00-18:00
Address: 3F Runyu Hall (3 楼润
宇厅)
Session SaO I-A: 14:00-15:00
[#1] A New Approach to Stabilization of Delayed Markov Jump Systems via Event-Triggered Control Wenqian Xie and Yuping Zhang, University of Electronic Science and Technology of China This paper investigates the stabilization problem for Markov jump systems with time-varying delay. Firstly, for reducing data transmission, we put forward a novel mode-dependent event-triggered communication scheme based on aperiodically sampled data. Secondly, a less restrictive Lyapunov-Krasovskii functional (LKF), which is only required to be positive definite at endpoints of each subinterval of the holding intervals, is firstly introduced for event-triggered control issue. Based on the above methods, a sufficient condition is obtained to ensure the stochastic stability and dissipativity of the resulting closed-loop system. Meanwhile, an explicit design method of the desired controller is given. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed method.
[#3] Image Completion Method Considering Content and Sharpness Ruqi Wang and Qun Liu, Chongqing University of Posts and Telecommunications The current image completion method can complete the missing image well, but they often fail to achieve better results when the missing area is at the edge of the image. In order to overcome this defect, this paper proposes a novel image completion method considering content and sharpness based on a generation adversarial network (GAN) and region growing algorithm. This model uses trained content and pixel joint discriminator to distinguish between real and generated images. The content discriminator focus on the entire image content to assess whether it is as coherent as a whole, and the pixel discriminator focus on the sharpness of the entire image to assess whether it is as same as the original image in sharpness based on multi-focus image fusion. A variety of missing blocks can be completed well by our method in dataset of Places2. In addition, compared to the other image completion method, this method can complete edge-loss blocks more excellently.
[#4] H∞ Control for T-S Fuzzy Systems with Aperiodic Sampling
Jinnan Luo, Wenhong Tian, Shouming Zhong and Daixi Liao, University of Electronic Science and Technology of China Jun Cheng, Qingdao University of Science and Technology Kaibo Shi, Chengdu University
This study focuses on the H∞ control for T-S fuzzy systems with aperiodic sampling. By utilizing the information of the state, an improved Lyapunov-Krasovskii functional (LKF) is constructed, together with free-weighted approach and aperiodic sampling techniques, further results are presented to ensure the T-S fuzzy systems to be asymptotically stable with H∞ performance γ. Moreover, the H∞ controller is devised with a larger sampling interval. Finally, a truck-trailer system is employed to affirm the effectiveness of the proposed results.
[#5] Speaker Identification Based on PCC Feature Vector Peichao He, Yi Zuo, Tieshan Li, He Ma and Junxia Liu, Dalian Maritime University C. L. Philip Chen, University of Macau In the research field of speaker identification, many extraction methods of speech feature have been investigated for several decades. However, several new features such as i-vector and d-vector were proposed in recent years. Mel Frequency Cepstral Coefficient (MFCC) is still wildly used in current speaker identification systems accounting for its high performance. Based on the similar generation approach of MFCC, this paper proposes a new method of feature extraction based on Pearson correlation coefficient (PCC). Firstly, we also use inverse discrete cosine transform (IDCT) cepstrum coefficient as the initial speech inputs. Secondly, we employ a hierarchical clustering analysis based on PCC to merge the IDCT cepstrum coefficient until the dimension of speech inputs is reduced to 14. Finally, we output this 14-dimensional vector as speech feature named r-vector. In the experiments, Gaussian Mixture Model (GMM) was used to compare the performance of r-vector with other speech features. According to the 630 people voice data in TIMIT database, the experimental results show that the r-vector can obtain higher recognition accuracy in speaker identification.
[#45] Impulsive Control with Time Windows for Hyperchaotic Exponential Synchronization Hongjuan Wu, Xiang Hu, Yuming Feng and Zhengwen Tu, Chongqing Three Gorges University In actual situation, the input error of impulsive signal is inevitable and there are always some time delays when different systems communicate with each other. Considering the input error and time delays, this paper, based on matrix inequalities, Lyapunov stability theory and impulsive control, put forward the criteria for the exponential synchronization of one type of hyperchaotic system via impulsive control with time windows.
17
Session SaO I-B: 15:00-16:00
[#7] Couple-Group Consensus for Cooperative-Competitive Heterogeneous Multi-Agent Systems with Pinning Control Ting Gao and Lianghao Ji, Chongqing University of Posts and Telecommunications In this paper, we investigate couple-group consensus of the heterogeneous multi-agent systems via pinning control method. A new control protocol is designed utilizing the cooperative-competitive interaction between the agents. In the framework of the weakly connected topology, the sufficient conditions and corresponding pinning strategies are obtained via several effective methods such as M matrix, Lyapunov stability theorem and graph theory and so on. The result shows that in order to achieve the couple-group consensus, the nodes with zero in-degree need to be pinned and the pinning gains of second nodes must satisfy the upper bound condition which we obtained. Finally, the effectiveness of the results is shown by simulations.
[#8] A Fast Method of Function Approximation Using Broad Learning System Yuzhuo Ma, Tieshan Li, Yi Zuo, Liangen Yuan and Qihe Shan, Dalian Maritime University C.L.Philip Chen, University of Macau In this paper, we apply the Broad Learning System (BLS) to approach function. Due to the complexity of the system in actual engineering, when the traditional algorithm handles the approximation problem, it faces problems such as complicated calculations and severe time consumption. To solve the above problems, the BLS uses the way of network horizontal expansion, horizontal extension and vertical immobility. Input data is mapped to feature nodes as feature vectors of the network, and then enhanced by the random weighted enhancement nodes, the enhancement nodes and feature nodes are merged together to connect to the output of the system. Finally, compared with traditional algorithms: back propagation neural network (BPNN), Radial Basis Function neural network (RBFNN), the results of experiments show that the function approximation method based on the BLS in this paper can make the system use less time under the premise of ensuring the approximation accuracy. This result provides the possibility of real-time and high-precision approximation for other intelligent algorithms.
[#9] An Adaptive Image Encryption Scheme Based on Bit-Level Permutation Ping Wang and Jin Qiu, Southwest University This paper proposes an adaptive image encryption scheme based on bit-level permutation. The plain image is firstly divided into 8 bit panels and then arrange into two groups. The permutation is performed on each group by a chaotic map relies on feature of the other group. After that, a keystream generated by another chaotic map is used to musk the image to get the cipher image. The proposed encryption scheme can resist chosen/known plain-image attack. Simulations have been carried out and the results indicate that our algorithm is efficient and highly secure.
[#10] Adaptive Consensus Control of Nonlinear Fractional-Order Multi-Agent Systems with a Leader Jiajun Yang, Wei Luo, Hao Yi and Wenqiang Xu, Chongqing University
In this manuscript, we investigate the adaptive consensus control problem of nonlinear fractional-order multi-agent systems with a leader. To solve the problem, an adaptive control protocol based on neighboring agent state information under undirected communication topology is presented. Then, according to the Lyapunov stability theory of the fractional order system, Barbalat lemma, Kronecker product and Schur complement lemma, the sufficient conditions for the researched systems to be consistent are obtained. Finally, the corresponding numerical simulation is given to verify the correctness of the obtained results.
[#11] A Delay System Approach to Networked Control System via an Event-Triggered Scheme Feng Hu and Xiaojie Su, Chongqing University This paper concerns a delay system approach to networked control system, this approach is based on a new delay model which contains multiple successive delay components in the state. The event-triggered mechanism is considered to reduce the workload of the communication network. Firstly, a new delay model with two successive delay components via an event triggered scheme is constructed, then results on stability and H∞ performance are proposed for networked control system by use of Lyapunov-Krasovskii functional. Finally, a numerical example is given to demonstrate the advantage of proposed result.
Session SaO I-C: 16:30-17:30
[#12] Robust Convergence of Uncertain Fuzzy BAM Neural Networks with Time-Varying Delays Wei Zhang, Liangliang Li and Yuming Feng, Chongqing Three Gorges University This paper focuses on the robust exponential convergence of uncertain Takagi-Sugeno (T-S) fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays. By employing Lyapunov method and delay inequality technique, several easily verifiable sufficient criteria are derived to guarantee the T-S fuzzy BAM neural networks with time varying delays to converge robustly exponentially to a ball in the state space with a pre-specified rate. Finally, a numerical example with simulations is given to illustrate the effectiveness of our theoretical results.
[#13] An Evolutionary Model of For-Profit Enforcement and Pervasive Law-Violation Kaiyue Wang, Tongkui Yu, Southwest University Xu Jin, Shandong University Pervasive law-violation, the committing of certain illegal behavior by most individuals, exists in many fields, such as the overloading of trucks, pollution-discharge of chemical companies, etc., in some societies especially developing economies. For-profit enforcement is considered to be one possible reason for this phenomenon. This paper reveals the causality using an evolutionary model. In this model, individuals are bounded rational, and decide on whether to abide a law by learning from each other in a short time horizon; the law enforcement agency, with higher rationality and the knowledge of individuals’ behavior evolution, will choose proper inspection frequency and punishment strength to maximize its payoff in a long time horizon. It is found that the best choice for law enforcement agency is not to investigate diligently and punish strictly, but to adopt lower inspection frequency and punishment strength, because this induces more individuals to violate the law and brings a
18
higher payoff for law enforcement agency. However, this intended lenient enforcement leads to a pervasive law-violation in the society. Possible solutions to this issue are discussed.
[#14] Differential Privacy Optimal Consensus for Multi-Agent System by Using Functional Perturbation Xiangyu Bu and Tao Dong, Southwest University Optimal consensus algorithm is a very useful algorithm for distributed cooperative control, which makes all of agents not only achieve consensus but also minimize the cost function. However, cooperative control requires that the agents exchange information in the public channel, which means that the information cannot be preserved well. If the information is sensitive, privacy disclosure of the individual agents may appear. To solve this problem, in this paper, a novel differential privacy optimal algorithm is proposed by adding functional perturbation. By using the convex properties, the mean square consensus conditions are obtained. Moreover, the privacy-preserving analysis is presented and the privacy level and the sensitivity of the differential privacy are also obtained. Finally, a numerical simulation is given to illustrate the effectiveness of the theoretical results.
[#47] Stabilization of Chen Chaotic System via Variable-Time Impulvise Control Ruihan Liu, Southwest University The stabilization of Chen chaotic system is studied in this paper. By variable-time impulsive control, the stabilization of the system could be achieved. Based on B-equivalence method, the controlled system is equivalent to a comparison system controlled by fixed-time impulse. Further, the Lyapunov function is constructed, which comes to the result that the controlled system tends to be exponentially stable. In the end, three groups of simulations with different initial values are presented to verify the effectiveness.
[#16] Intermittent Impulsive Consensus of Multi-Agent Systems Kun Li, Tiantian Yu, Zhengle Zhang and Tiedong Ma, Chongqing University The intermittent impulsive consensus of multi-agent systems is studied in this paper. In order to solve the problem of unreliable communications, we adopt an intermittent impulsive control algorithm to achieve consensus of multi-agent systems. In this paper, impulsive control is only taken in the control windows, not during the whole time. Based on Lyapunov stability theory, the novel sufficient condition is derived to realize the intermittent impulsive consensus of multi-agent nonlinear systems. Finally, a simulation example is given to show the effectiveness of intermittent impulsive control method.
Session SaO I-D: 17:30-18:00
[#17] Double Closed-Loop Control Strategy for Electric Springs Based on PI Controller Yun Zou, Shihao Xu and Michael Z. Q. Chen, Nanjing University of Science and Technology Electric Springs (ESs) can effectively solve the problem of load side voltage instability caused by the voltage fluctuation on the grid side. Although the single closed-loop control strategy based on the root mean square (RMS) value of the voltage at the point of common coupling (PCC) can maintain
the PCC voltage stability, the harmonics on the load side and the ES output voltage will be distorted largely. In this paper, a double closed-loop control strategy with an outer voltage loop and an inner current loop is proposed to address the problem mentioned above. The simulation results show that the improved double closed-loop control strategy can effectively suppress the harmonics on the PCC voltage as well as the ES output voltage.
[#18] Balanced Performance Preserving Model Reduction for Uncertain Semi-Markovian Jump Systems: Continuous-Time Case Huiyan Zhang, Wengang Ao, Shuai Yang and Peng Shi, Chongqing Technology and Business University This paper investigates the model reduction problem for continuous-time phase-type semi-Markovian jump systems (PH-SMJSs) based on balanced truncation method. The time varying delay is considered using Wirtinger-based integral inequality and the parameter uncertainties are assumed to be randomly occurring. By utilizing the generalized output and input dissipation inequalities, the generalized gramians are solved. And the balanced realizations of the original PH-SMJSs are yielded according to the abilities of the controllability and observability. Then the low-order models are found by state truncation technique. Furthermore, the balanced performances of the original PH-SMJSs are preserved in the reduced-order models. Simulation results are conduced to illustrate the effectiveness of the proposed model reduction methods for SMJSs.
[#21] Improving Prediction Accuracy of Protein Content in Corn by Using the Multi-Population Genetic Algorithm and Partial Least Squares Yongchao Wu and Guangyuan Liu, Southwest University Although the combination of genetic algorithm and partial least squares (GA-PLS) was successfully used to predict the protein content in corn，there is the problem of premature convergence for the genetic algorithm。In the paper，we replaced the genetic algorithm by the multi-population genetic algorithm to form the combination of multi-population genetic algorithm and partial least squares (MPGAPLS) to improve the prediction accuracy of the protein content in corn from near infrared spectrum。Based on the public data set which include the protein content and near infrared spectrum for 80 corn samples，we divided the whole near infrared spectrum into 20 intervals， and the infrared spectrum data in 5 intervals were chosen as prediction features by their root mean square errors in the partial least models which transformed infrared spectrum data in each interval into corresponding protein content。Using the infrared spectrum data in the chosen 5 intervals and protein content for the 80 samples，we randomly chose 60 samples for training and 20 samples for testing to compare the GA-PLS and MPGA-PLS by 30 repetitions。Compared with the GA-PLS，the prediction accuracy of MPGA-PLS is significantly improved by 1.88 (P=0.001)，and the mean prediction correlation coefficient (CC) is 0.9730。The result illustrates that the proposed MPGA-PLS improved the prediction accuracy of protein content in corn，and may be effectively used into nondestructive testing protein content from near infrared spectrum in many other applications.
19
Saturday, September 28, 2019
Session SaO II: 14:00-18:00
Address: 3F Keyu Hall (3 楼科宇
厅)
Session SaO II-A: 14:00-15:00
[#48] An Optimal Transmission Channel Selection Algorithm for Emergency Communication Xidong Zhang, Beijing Jiaxun Feihong Electrical Co., Ltd Heng Zhang, Institute of Army Aviation Wenhong Liu, Jiaxun Feihong Intelligent Technology Institute Baojun Song, Jiaxun Feihong Intelligent Technology Institute Hongbo Zhang, Beijing Jiaxun Feihong Electrical Co., Ltd. Shujie Zhu, Beijing Jiaxun Feihong Electrical Co., Ltd. An optimal transmission channel selection algorithm based on AHP (Analytical Hierarchy Process) aiming at fulfilling the demand of emergency communication scenario is proposed in this paper. In the process of the algorithm, a Specifications Vector Library is set up based on communication requirement presetting, meanwhile, a Weight Vector Library is set up according to the definition of the importance of the specifications. By matching the available network channel resources and the two Vector Libraries, a communication link scheme is produced with an AHP based decision making process to strike a balance between transmission efficiency and economy under the restraint of the available communication network channel resource condition.
[#23] Evolutionary Model of Braess’s Paradox and the Optimal Solution by Charging Xianping Yu, Kaiyue Wang, Xin Wang and Tongkui Yu, Southwest University The Braess’s paradox is the phenomenon that increasing the resources leads to the reduction of the overall welfare, originally proposed in the field of transportation. An evolutionary game model is proposed to explicitly depict the process of individual learning in this phenomenon. It shows clearly how the individual rationality leads collective irrationality. A proper charging scheme is provided which can not only solve the Braesss paradox, but also maximize social welfare. This work provides inspiration for the policy to guide the self-interested individuals to achieve social welfare maximization.
[#24] A Kernel Recursive Mixed Error Criterion Algorithm for Chaotic Time Series Prediction Qishuai Wu, Wanlu Shi, Xinqi Huang and Wei Xue, Harbin Engineering University Yingsong Li, Harbin Engineering University, National Space Science Center, CAS In this paper, a kernel adaptive algorithm, named as kernel recursive mixed error criterion algorithm (KRMEC), is proposed in the context of nonlinear signal processing, which
uses two different error schemes to construct a new cost function that is created by two-order error and generalized maximum correntropy criterion (GMCC). The proposed KRMEC algorithm is used for chaotic time series prediction (CTST) under non-Gaussian noise environment. Simulation results show the desirable performance of the proposed KRMEC algorithm.
[#25] Network Community Detection Using a Backtracking-Based Discrete State Transition Feng Zhang, Changsha University of Science and Technology Ke Yang, Xiaojun Zhou and Chaojie Li, Central South University Detecting communities in networks (i.e. community detection) is a famous topic in the field of network science. In the last decade, many community detection approaches based on evolutionary computation have been designed and attracted much attention. Recent years, a new evolutionary algorithm called state transition algorithm (STA) has been proposed. In our previous work, a population-based discrete STA (MDSTA) has been put forwarded to solve the community detection problem. Similar to most population-based evolutionary algorithms, MDSTA has a relatively complex algorithm structure which may limit the application of the algorithm. To address this problem, a back tracking based discrete STA (BDSTA) is proposed in this paper. BDSTA is a kind of individual-based algorithm, and two kinds of substitute operators based on the label-based representation and the locus based representation are used in BDSTA for global search and local search, respectively. Owing to that the individual-based algorithms often fall into a stagnation solution, we employ a backtracking search strategy in the global search procedure. Finally, five real-world networks and the extended GN artificial networks are used to evaluate the performance of BDSTA and some state-of-art algorithms. Experimental results prove that BDSTA can find the community structure with high quality and is more efficient than these state-of-art algorithms.
[#26] Association Rules Hiding via Multi-Objective Differential Evolution Algorithm Nankun Mu, South China University of Technology, Southwest University Fan Yang, Southwest University Association rules (ARs) mining has been widely used in discovering interesting patterns from massive data as a key data mining technique. However, this mining technique may lead to the disclosure of sensitive ARs, and thus, the ARs hiding strategy is very important and necessary. In this paper, a novel ARs hiding method (DEvoArH) is proposed for hiding the ARs. Noting that there are three side-effects in ARs hiding (ARH), i.e., the hiding failure rate, the lost rules rate, and the ghost rules rate, a multi-objective differential evolution algorithm is carefully designed. Specifically, the Pareto-optimal solutions are defined as the elite set, and then each solution is capable of learning from the elite set with a certain probability. Considering the convergence speed and search ability, a directional mutation and random mutate round is introduced into the mutation operator. Besides, to further decrease the data change rate, a database pre-processing mechanism is proposed to filter the unrelated data before the hiding process. Finally, the results of the comparison experiments also demonstrate the superiority of the proposed ARH method in terms of the three side-effects and efficiency.
20
Session SaO II-B: 15:00-16:00
[#27] Feature Space Oversampling Technique for Imbalanced Classification Haoyang Wang and He Huang, Soochow University Imbalanced classification problems are very common in real world. With traditional classification methods, it is generally difficult to obtain satisfactory classification results. Oversampling method is one of the popular methods for this kind of problems. Existing oversampling methods usually only select the borderline minority samples to over-sample. In this way, there are a large number of synthetic minority class samples in the boundary region, which would destroy the original boundary. To overcome this issue, a feature space oversampling technique (FSOTE) is proposed in this paper. The FSOTE algorithm can find the minority class clusters from the feature space, and the synthetic samples in the minority class are filled in the interior of these clusters. Experimental results show that the algorithm can efficiently improve the classification performance on imbalanced data sets than some existing ones.
[#28] Stability Analysis on Variable-Time Impulsive Networks Renyi Xie, Chuandong Li, Zhengran Cao and Zhilong He, Southwest University In this paper, the stability of the time-varying impulsive Cohen-Grossberg network is investigated. During the given surface interval, we consider the two intersections. Firstly, the conditions that guarantee the subsystem hits the surfaces once or twice are presented. In addition, we get the further study on the asymptotic stability. By using Lyapunov function, we have the specific condition for the impulsive network. Especially, based on our analysis, we could choose proper surfaces and impulse function to make the network stable at the origin. Finally, two simulation results testify the effectiveness of the theoretical results we get.
[#29] Second-Order Wheeled Mobile Robot Based on Fractional-Order PD Controller Xuchen Wang, Lu Liu, Yuxuan Huang, Qiuyue Wang, Pan Qi and Gang Lu, Northwestern Polytechnical University The paper proposes the second-order wheeled mobile robot control by using the fractional-order PD. The wheeled mobile robot (WMR) has nonholonomic properties and uncertainties brought on by the internal dynamics and/or feedback sensors. In previous work, the PD controller can not present the precise controlofspeedduringtheprocessoftracking,whichmay lead to the failure of path tracking. To overcome this problem, we propose a robust robot fractional-order proportional-derivative (FOPD) controller for WMR trajectory tracking. To verify the feasibility and effectiveness of our proposed FOPD controller, we design the simulation and experiment for classical PD controller and FOPD controller. The comparative results show that FOPD controller provides better tracking performances.
[#30] Input-to-State Stability of Impulsive Stochastic Nonlinear Systems with Lyapunov Indefinite Derivative Chenghui Mao, Southwest University The properties of input-to-state stability (ISS), integral input-to-state stability (IISS) and stochastic input-to-state stability (SISS) are discussed for impulsive stochastic nonlinear systems with Lyapunov indefinite derivative in this paper.
The Lyapunov time derivative is indefinite, it can be positive or negative, which means it can be applied to a wider range than other ordinary Lyapunov function. Through the use of average dwell-time (ADT) method, the ISS, SISS and IISS properties are derived in the paper. By now, there is no literature on such properties of nonlinear impulsive stochastic systems with Lyapunov indefinite derivatives. In the end, an example is presented to illustrate the validity of this outcome.
[#31] Global Exponential Stability of Memristive Complex-Valued Neural Networks with Mixed Time Delays and Impulse Effects Xuejun Wang, Southwest University In this paper, based on inequality techniques and Lyapunov’s second method, Global exponential stability (GES) problem of memristive complex-valued neural networks (MCVNNs) is discussed. The MCVNNs may be unstable due to time delay and impulsive effects. Therefore, we considered the influence of these two factors on the MCVNNs. For obtained the desire results we divide MCVNNs into two real-valued parts. Some new conditions are acquired to ensure the MCVNNs is stable. At the last, the simulations of real and imaginary parts are afforded to show the validity of the results by an example.
Session SaO II-C: 16:30-17:30
[#32] Consensus Analysis Based on Saturated Impulsive Control in Networked Multi-Agent Systems Xinmiao Dong, Southwest University This paper mainly investigates the self-feedback and leader-following consensus of multi-agent networks under saturated impulsive control. Based on Laplacian matrix, convex analysis and Lyapunov stability theory, some conditions are proposed for multi-agent networks to reach exponential asymptotic consensus, and the convergence rate is calculated by mathematical induction and differential equation. Finally, two simulations are given to validate the correctness of the analysis.
[#33] Couple-Group Consensus for Heterogeneous Multi-Agent Systems with Event-Triggered Methods Jianlei Xu, Shasha Yang, Qianzhu Wang and Lianghao Ji, Chongqing University of Posts and Telecommunications A scenario of cooperative and competitive interactions in heterogeneous multi-agent networks is described in this paper. Several reasonable control protocols are proposed through event-triggered actuation schemes. According to the knowledge of matrix analysis and algebraic graph theory, the trigger functions for the multi-agent systems are designed. Moreover, the sufficient conditions that enable the particular heterogeneous multi-agent systems to realize couple-group consensus are presented by adopting the Lyapunov stability theorem. Lastly, the validity of the theoretical analysis is confirmed by the simulation.
[#34] Existence and Stability Analysis of Periodic Solution of FitzHugh-Nagumo Neuron Model with State-Dependent Impulse Effects Cong Liu, Southwest University In this paper, a new hybrid neuron model is proposed by combining FitzHugh-Nagumo neuron model with impulsive effect. The properties in the neighborhood of the equilibrium point of the system are qualitatively analyzed. Based on the theory of impulsive semi-dynamical system, the poincar´e
21
map is established by using the poincar´e section and the geometric theory of ordinary differential equation. Several sufficient conditions for the existence of order-1 periodic solution, order-2 periodic solution and orbital asymptotic stability are obtained. Some simulation examples are given to demonstrate the correctness of our theory.
[#35] A Distributed Dynamic Resource Allocation Strategy in a Large-Scale Micro-Grids Group Zao Fu and Xing He, Southwest University In this paper, a dynamic economic dispatch problem (DEDP) with renewable energy generators is studied. With the purpose of minimizing the cost of DEDP and optimally allocate the load demand among the interconnected generators considering ramp-rate limits and generation limits, an effective continuous-time distributed algorithm based on interior point methods and primal-dual methods is proposed. In order to overcome the drawbacks of the renewable energy, a parallel system composed with flywheel energy storage systems and renewable energy generators is proposed to work in a constant power output mode. In addition, the using of switched systems makes the optimal solution more accurate. The excellent performance of the proposed algorithm is verified by IEEE 30-bus system with the REG based simulation.
[#36] A Recurrent Neural Network for Optimal Energy Management Considering the Battery Cycle-Life in Smart Grid Miao Sun, Southwest University, Fudan University Xing He, Southwest University This paper proposes a combined battery energy management (CBEM) model against the background of smart grid, which focus on the absorptive ability of Battery Energy Storage System (BESS) distinguishing to the traditional energy management. To solve the CBEM model, an one-layer recurrent neural network (RNN) is recommended. Furthermore, by considering the peak and valley periods division prices, the generators absorption and the distribution network bought from power grid are optimized. Meanwhile, the emission cost is considered in total cost and there is a corresponding constraint to control the emission and the outputs of generators. Finally, the effectiveness of the CBEM model is verified on Matlab. With the fluctuation of electrical price, the charge model and discharge model of BESS are showed. Results indicate that this model performs well in cutting the load in peak time and storage energy in valley time.
Session SaO II-D: 17:30-18:00
[#37] A Shrinkage Correntropy Based Algorithm under Impulsive Noise Environment Wanlu Shi, Harbin engineering university Yingsong Li, National Space Science Center, Chinese Academy of Sciences For the problem that the signals measured in the fault, the maximum correntropy criterion (MCC) algorithm shows good capacity in non-gaussian environment. Recently, a MCC algorithm uses shrinkage technique, namely the noise free maximum correntropy criterion (NFMCC) has been proposed, which reduces the mean square deviation (MSD) significantly. In this paper, a reweighted l1-norm penalized shrinkage maximum correntropy criterion (RL1-SMCC) is derived in detail. The new algorithm considers the norm
penalty to exploit the sparse nature in various systems. Hence, the proposed algorithm provides an excellent behavior for sparse as well as non-Gaussian systems. The cost function of the proposed algorithm is constructed based on the correntropy theory which is implemented by a normalized Gaussian kernel. What’s more, the norm penalty is integrated into the cost function aiming to take advantage of the sparse character. Finally, based on the shrinkage method, an alterable convergence step is obtained which enables the algorithm to converge fleetly. To evaluate the RL1-SMCC algorithm, several examples for system identification in non-Gaussian environment are set up which show the validity of the proposed algorithm.
[#38] Image Classification Based on Convolutional Neural Nework and Support Vector Machine Nankun Mu, South China University of Technology, Southwest University Dewen Qiao, Southwest University Automatic classification of images is a key task in many areas, including information retrieval, scene detection, internet data filtering, medical applications, etc. When directly operating on the image, the traditional classification method is difficult to achieve good results due to the high-dimensional characteristics of the data. To this end, in this paper, a novel method of image classification named CNN-SVM is proposed. Specifically, we first preprocess original images to extract the vital features and reduce redundant features by using the convolutional neural network (CNN). Then, the crossvalidation (CV) is adopted to optimize the penalty parameter C and the kernel parameter σ for the support vector machine (SVM). Finally, the extracted features will be input to an optimized SVM model. In order to validate the superiority of our proposed algorithm, we select a hybrid image set taken from Caltech 265 image archive as our experimental data. The experimental results reflect that CNN-SVM has higher classification accuracy.
[#39] The Kernel Recursive Generalized Cauchy Kernel Loss Algorithm Wei Shi, Kui Xiong and Shiyuan Wang, Southwest University As a nonlinear measure similarity developed in the kernel space, the generalized correntropic loss (GC-Loss) is widely used in non-Gaussian signal processing and machine learning thanks to its ability to extract high-order data statistical properties. However, the performance surface of GC-Loss is highly non-convex, which can be very sharp around the optimal solution while extremely flat at a region far away from the optimal solution. This high non-convexity may result in poor convergence performance in adaptation. To address this issue, we propose a new similarity measure developed in the kernel space by combining a generalized Gaussian distributed kernel function into the Cauchy loss. By minimizing the proposed loss function and using the kernel trick, we propose a novel kernel recursive generalized Cauchy kernel loss (KRGCKL) algorithm in the reproducing kernel Hilbert space (RKHS). Simulations on different examples under non-Gaussian noises show the superiorities of KRGCKL over other representative algorithms in terms of filtering accuracy and robustness.
22
Saturday, September 28, 2019
Session SaO III: 14:00-18:00
Address: 2F VIP Hall (2 楼贵宾
厅)
Session SaO III-A: 14:00-15:00
[#49] Robust Manhattan Non-Negative Matrix Factorization for Image Reconstruction Xiangguang Dai, Wei Zhang and Yuming Feng, Chongqing Three Gorges University Non-negative matrix factorization (NMF) and its improvement methods fail to image reconstruction while the image dataset is corrupted by saltand pepper noise. In this paper, robust Manhattan non-negative matrix factorization (RMahNMF) based matrix completion is proposed to restore the corrupted data. Experiments show that RMahNMF is more effective and robust in image reconstruction than other NMF methods.
[#50] Expenential Synchronization of Memristive Cohen-Grossberg Neural Networks with Mixed Time Delays Yinghua Zhou, Jiamin Quan, Hongyi Liu and Huiyu Nie, Southwest University This paper is concerned with the problem of global exponential synchronization for a class of impulsive memristive Cohen-Grossberg neural networks with mixed time delays. By applying the impulsive functional differential equations, constructing suitable Lyapunov function and contradiction method, several corresponding easy-to-check criteria are derived. Moreover, the conditions established in this paper are easy to be verified and improve the conditions derived in most of existing papers concerning stability and synchronization for impulsive memristive neural networks. Finally, a numerical example is given to illustrate the effectiveness of the theory.
[#42] A Simple Motion Deblurring Method by Two Continuous Images Jihai Zhang, Jianfeng Li, Guangyuan Liu, Tong Chen, Tengteng Zhu and Bo Li, Southwest University Restoring blurred images to clear images is a challenging problem. Most previous methods only analyzed the single image. However, for motion blurring, this method missed the key trajectory description process. Based on the essence of motion blur, our research combined the continuous frame image information in video to estimate the motion track, the SIFT algorithm was proposed for the first time to match the feature points of the target in the continuous frame image. The accurate motion blur angle and motion blur distance were obtained by combining the matching information to obtain an accurate PSF. Finally, the Wiener filtering algorithm combined with PSF was used for deblurring. Experiments showed that the proposed method can improve the image sharpness after restoration compared with the previous algorithms.
[#51] A Nonlinear Impulsive Control System with Impulse Time Windows and Un-Fixed Coefficient of Impulsive Intensity
Yuming Feng, Xiaoyu Liu, Zitao Wang and Wei Zhang, Chongqing Three Gorges University Based on the fact that there always exists error in the impulsive intensity, which leads to the fact that the coefficient is un-fixed, and in the occurrence of the impulses, we propose a new model, which is called nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity. We find sufficient conditions for ensuring its stability by using Lypunov’s method. We choose chaotic Lorenz system and Chua’s system as numerical examples to show the effectiveness of the results, by employing such method, the systems are controlled.
[#44] Stability of Stochastic Systems with Variable-Time Impulses Jie Tan and Zhaohui Chen, Chongqing University of Science and Technology This paper studies the stability of stochastic systems with variable-time impulses. By B-equivalence method, we consider the case that the trajectory of the stochastic system intersects each surface of discontinuity exactly once. Then we shall show that under the well-selected conditions the variable-time impulsive systems can be reduced to the fixed-time impulsive ones. Based on the stability theory of fixed-time impulsive stochastic systems, we propose a set of stability criteria for the variable-time impulsive systems. The effectiveness of the theoretical results are illustrated by two numerical examples.
Session SaO III-B: 15:00-16:00
[#6] Row-Stochastic Matrices Based Distributed Optimization Algorithm with Uncoordinated Step-Sizes Huaqing Li, Jinmeng Wang and Zheng Wang, Southwest University This paper investigates the distributed optimization problem over multi-agent networks, in which the target of agents is to collaboratively optimize the sum of all local objective functions. Each local objective function is uniquely known by a single agent. We concentrate on the scenario where communication among agents is portrayed as directed graphs. Based on the exact first order method, a fully distributed optimization algorithm is proposed to solve the optimization problem. The proposed algorithm utilizes row-stochastic matrices and uncoordinated step-sizes, which exactly drives all agents to converge to the global optimization solution. Under the assumptions that the global objective function is strong convex and the local objective functions have Lipschitz continuous gradient, we show that the proposed algorithm linearly converges to the global optimization solution as long as the maximum step-size of agents does not exceed an explicitly characterized upper bound. Finally, numerical experiments are presented to demonstrate the correctness of theoretical analysis.
[#15] Secure Consensus Control for Time-Varying Multi-Agent Systems with Mixed Types Attacks Xiaomeng Li, Wenbin Xiao, Qi Zhou and Hongyi Li, Guangdong University of Technology This paper addresses the finite-horizon secure consensus control problem for time-varying multi-agent systems (MASs) subject to randomly occurred attacks. A more general mixed types attacks model is proposed to describe the denialof-service (DoS) and false data injection (FDI) attacks at cyber layer in a stochastic way. Specifically, DoS and FDI attacks
23
are considered for measurement and control channels, and they are assumed to obey Bernoulli process. Two sufficient criteria are obtained to ensure that the time-varying MASs achieve consensus with a prescribed H∞ performance. Then, by solving recursive matrix inequalities (RLMIs), the parameters of the controller are derived. Finally, the usefulness of the developed consensus control protocol is verified by utilizing simulation example.
[#22] A Self-Learning Sliding Mode Controller for Biological Wastewater Treatment System XiaolongWu, Honggui Han and Junfei Qiao, Beijing University of Technology The control system, as an important part in biological wastewater treatment system (BWTS), is employed to meet the operational goals for reaching required effluent quality; however, the control performance will be degraded under drastic uncertainties and various conditions. In this paper, a self-learning sliding mode controller (SLSMC) is proposed for BWTS without the knowledge of uncertainties. First, a mathematical kernel function (MKF) is established to estimate the bounds of uncertainties, which is used to pursue the optimized control law of SLSMC. Second, a self-learning optimization algorithm is designed to modify the parameters of MKF, which ensure that there is no overestimation parameters of SLSMC. Third, a gain adaptation mechanism, based on MKF and conventional conditions of BWTS, is developed to suppress the chattering and maintain control accuracy simultaneously. Finally, to show the effectiveness of SLSMC, it is applied to BWTS under uncertainties and different conditions in comparison with other existing methods. The results demonstrate that SLSMC performs favorably in terms of both chattering reduction and control accuracy.
[#40] Raman Imaging Data Preprocessing for Quantitative Analysis Waihou Ao and Long Chen, University of Macau Raman spectroscopy is an essential component in spectroscopy and materials science. It is also widely used in the field of chemistry. However, Raman spectrum is hard to precisely observe because of the interference of noises. This may lead to an inaccurate analytic result. Therefore, an effective preprocessing method is indispensable for Raman spectrum analysis. In this paper, we focus on preprocessing Raman imaging data of a mixture, which is consisted of two substances. We will calculate an intensity value for each of them from thousands of spectrums. The preprocessing algorithm can be divided into four parts: normalization, noise reduction, background removal and peak detection. First of all, we scale the input data so that all value is within the range of 0 and 1. After that, we use Savitzky–Golay filter to denoise and remove the fluorescence background of the Raman spectrum. Finally, we identify the peak positions and measure its value of the Raman spectrum. As a result, we can quantify the intensities of two substances and use their ratio to estimate the composition ratio in the mixture.
[#41] A Multifunctional and Robust Learning Approach forHuman Motion Modelling Chunyang Zhang, Yongyi Xiao and Jiaqi Pu, Fuzhou University Human motion modelling plays an important role in the automation of the robot systems, including human motion recognition and generation. The problem is often intractable since it requires high-dimensional sequential data modelling
as well as capturing both spatial and temporal correlations from motion videos. In the paper, a multifunctional and robust learning approach called broad conditional restricted Boltzmann machine (BCRBM) for human motion modelling is introduced, which employs CRBM for motion generation and broad learning system (BLS) for motion recognition. The proposed hybrid broad CRBM model has many advantages from four aspects. (1) This one off trained model can be simultaneously employed to recognize and generate human motions with outstanding performance; (2) Without deep architecture and with the help of broad learning system, it shows out better capability in different motion generation and recognition over deep models; (3) It is more efficientasits learning process no longer need the time-consuming two-phases learning ,namely pre-training and fine-tuning for deep models; (4) It is still a probabilistic graph model that has better robustness for noisy samples compared with deterministic models. These advantages are both verified and evaluated with a number of experiments, where 2D MOCAP datasets are employed.
Session SaO III-C: 16:30-17:30
[#43] Robust H∞ Control Based on Event-Triggered Optimization Jiajie Lu, Yuan Fan and Teng Li, Anhui University
For linear systems, the robust H∞ control under the event-triggered optimization mechanism is studied. Firstly, under the time-triggering and event-triggering mechanism, the system optimization performance index is given and the optimized controller is designed. Then, consider the robust H∞ control based on the event-triggered optimization
mechanism. When the external interference is zero, the proof of the asymptotic stability of the linear systems is given. When the external interference is not zero, the system has interference suppression level γ of H∞ control. Then, the Zeno behavior of the linear system is analyzed, and a positive minimum event-triggering time interval is given by derivation to ensure that the Zeno behavior does not exist in the system. Finally, the effectiveness of the algorithm is verified by system simulation.
[#46] Rotating Consensus Control of Double-Integrator Multi-Agent Systems under Directed Graphs Rui Ding and Wenfeng Hu, Central South University This paper addresses the rotating consensus problem for a group of double-integrator agents under directed graphs. Provided that the direct graph has a spanning tree, the distributed control law is proposed to guarantee that each agent not only is drived to achieve the consensus with respect to velocity and circle center but also form a circular motion. Evidently, numerical simulations show that the control law can efficiently solve the rotating consensus problem under directed graphs.
[#52] Planning PEV Fast-Charging Stations: A Data-Driven Distributionally Robust Optimization Approach Bo Zhou, Yuefei Yuan and Huiwei Wang, Chongqing Jiaotong University In this paper, a novel fast-charging station planning model is established based on data-driven distributionally robust optimization approach, which aims to minimize expected costs for both transportation network and distribution network. A statistical measure named φ-divergence is employed to establish the service ability constraints for the
24
sizing problem. On the other hand, a modified capacitated flow refueling location model is constructed to develop the siting constraints for the siting problem. In addition, AC power flow model is investigated to model the operation of distribution network with the penetrations of fast-charging stations. A case study is conducted to illustrate the effectiveness of the proposed planning model.
[#53] Integrated Pest Managements in a Pest-Natural Enemy System with Adaptation of Pest Yi Yang, Chongqing Three Gorges University Changcheng Xiang, Hubei Minzu University Shasha Yan, Chongqing Jinshan Science and Technology Company In this paper, we expanded the classic LotkaVolterra prey-predator model, and mainly focused on the dynamic behavior of pest-natural enemy system with integrated pest managements, and the pest could choose either risky or safe mode to adapt with the varying environment.
[#54] Lagrange Stability Analysis for Quaternion-Valued Memristive Neural Networks Zhengwen Tu, Liangwei Wang, Tao Peng, Liangliang Li and B. O. Onasanya, Chongqing Three Gorges University In this paper, the problem of global Lagrange stability for quaternion-valued memristive neural networks (QVMNNs) with time-varying delays is investigated. Based on the direct approach, Lyapunov function and inequality techniques, some succinct criteria are proposed to guarantee the QVMNNs to be globally exponentially stable (GES) in Lagrange sense. Meanwhile, estimations of the global attractive set are given out. Finally, simulation examples are presented to elucidate the effectiveness of theory results.
Session SaO III-D: 17:30-18:00
[#55] Error-Correcting Performance Comparison for Polar Codes, LDPC Codes and Convolutional Codes in High-Performance Wireless Chao Yang, Ming Zhan, Yi Deng, Meng Wang, Xiaohong Luo and Jie Zeng, Southwest University In this paper, polar codes, low-density paritycheck (LDPC) codes and convolutional codes in the status of high-performance wireless (WirelessHP) are discussed. Those classic code schemes are compared in terms of their encoding and decoding complexity and error-correcting performance. Results show that, polar codes with successive cancellation list (SCL) decoding is superior to the LDPC codes and the convolutional codes in the condition of WirelessHP. The result has certain significance for the development of next generation communication technology.
[#56] The Projective Synchronization of a HX-Type Hyperchaotic Hyperjerk System Baojie Zhang, Chongqing Three Gorges University In this paper, we investigate the projective synchronization of a HX-type hyperchaotic hyperjerk system based on a hyperchaotic hyperjerk system. For this purpose, switching backstepping sliding mode control method is utilized. Simulation illustrates the effectiveness of the control method.
[#57] Annual Runoff Forecast Based on Cooperative Particle Swarm Projection Pursuit Regression Model Xinxin Li and Jing Xu, Xinjiang Agricultural University
According to the high-dimensional nonlinear problem of annual runoff prediction, to build runoff forecasting model based on projection pursuit regression model of Hermite polynomials and the cooperative particle swarm optimization algorithm. Projection pursuit prediction model projects high dimensional data into low-dimensional space based on sample data driving, completely according to the sample data driven to enhance the prediction results objectivity. The particle swarm optimization algorithm combines the idea of co-evolution to optimize the projection direction and polynomial coefficients in parallel, and further improve the convergence rate and prediction accuracy of the model. The model is applied to the flow prediction of Jiubujiang River Reservoir. The relative error of runoff prediction is less than 15%, and the prediction result is high precision and reliability. The experimental results show that it is feasible and effective to use the cooperative particle swarm projection pursuit regression model to predict the annual runoff.
25
Keynotes
September 29; 3F Guohui Hall (3 楼国会厅)
Chair: Qiankun Song
Time Title Author Institution
08:30–09:00 基于强化学习的热液喷口搜索与水
下机器人运动控制 宋士吉 清华大学
09:00–09:30 网络系统协同抗干扰控制 虞文武 东南大学
09:30–10:00 压电陶瓷执行器的智能控制方法 程龙 中国科学院
10:00–10:30 Coffee break
10:30–11:00 航天器自主控制研究进展汇报 胡庆雷 北京航空航天 大学
11:00–11:30 复杂脉冲控制理论及相关应用 李晓迪 山东师范大学
11:30–12:00 核熵学习理论与方法 陈霸东 西安交通大学
14:00–14:30 基于主角保持性质的压缩 子空间学习 谷源涛 清华大学
14:30–15:00 基于多模态深度学习的脑网络方法
与脑疾病辅助诊断 李阳 北京航空航天 大学
15:00–15:30 复杂网络迭代学习控制若干 问题研究 熊文军 西南财经大学
15:30–16:00 协同学习系统：概念、架构和算法 郭平 北京师范大学
16:00–16:30 Coffee break
16:30–17:00 数据驱动优化、建模与应用 李超杰 哈马德-本-哈利法
大学
17:00–17:30 复杂噪声情况下的新型卡尔曼 滤波器研究 黄玉龙 哈尔滨工程大学
17:30–18:00 基于可变 q 梯度的主动噪声 控制算法研究 赵海全 西南交通大学
26
报告题目:基于强化学习的热液喷口搜索与水下机器人运动控制
报告人: 宋士吉 清华大学
宋士吉简介:
宋士吉，男，1965 年 5 月生，黑龙江省富锦市人，清华大学自动化系教授、博
士生导师。2000 年以来在清华大学自动化系和国家 CIMS 工程技术研究中心从
事教学与科研工作。1996 年获得哈尔滨工业大学基础数学专业博士学位；1996
至 2000 年，分别在中国海洋大学物理海洋专业和东南大学控制理论与应用专业
先后两次完成博士后研究。长期致力于生产制造复杂工艺过程的建模与随机优
化及智能调度方法、机器学习理论方法及其应用、水下机器人智能控制与探测
技术等方向研究，在国内外重要学术期刊会议发表论文 240 余篇，其中 IEEE
Transactions 系列期刊长文、国际著名期刊等 SCI 检索论文 120 余篇；担任
《IEEE Transactions on Systems, Man, and Cybernetics:Systems》编委，国际期刊
《The Scientific World Journal-Operationas Resarch》编委；《Artificial Intelligence
and Robotics Research》副主编，《Mathematics Review》评论员；曾任《中国科
学-信息科学》与《自动化学报》等期刊编委。
近五年来，主持国家自然科学基金重大科学仪器研制项目、铁联合基金重点项
目、面上项目、科技部 863 项目、教育部博士点基金、中国大洋矿产资源研究
开发协会专项等累计 20 余项。 先后获得江苏省自然科学一等奖、中国自动化学
会教学成果一等奖、教育部高等学校自然科学二等奖奖、英国皇家工程授予的
“Distinguished Visiting Fellowship”奖。
报告题目：网络系统协同抗干扰控制
报告人：虞文武 东南大学
虞文武简介:
虞文武，1982 年生，2004 年和 2007 年分别在东南大学获得学士和硕士学位，
2010 年在香港城市大学电子工程系获得博士学位。东南大学教授（首批青年首
席教授），数学、网络空间安全、控制科学与工程、统计学等学科研究生导师；
江苏省网络群体智能重点实验室常务副主任、网络空间安全学院复杂网络应用
与安全研究中心主任、澳大利亚 RMIT 皇家墨尔本理工大学客座教授；入选国
家“万人计划”青年拔尖人才、教育部“长江奖励计划”青年学者、国家优秀青年
27
科学基金获得者；2014-2018 连续五次入选科睿唯安/原汤森路透全球高引科学
家（工程学）。主要从事复杂网络系统协同分析、控制、优化及其应用（复杂网
络与复杂系统、多智能体系统、神经网络、网络系统控制与优化、网络智能与
安全控制、无人系统、智能电网、智能交通、物联网与智慧城市、大数据分析）
等相关研究，Springer 合编书和 Wiley专著各 1部，发表 IEEE汇刊、Automatica、
SIAM 杂志论文近 100 篇；Google 引用过万次，SCI他引 7000 余次，SCI H指数
47；32 篇 ESI 高被引论文(学科前 1%)。担任 IEEE Trans. Industrial Informatics
(SCI IF: 7.358)、IEEE Trans. Systems, Man, and Cybernetics: Systems (SCI IF: 7.351)、
IEEE Trans. Circuits and Systems II (SCI IF: 3.250)、中国科学信息科学 (SCI IF:
2.731)和中国科学技术科学 (SCI IF: 2.180)等杂志编委；曾获国家自然科学二等
奖 1 项（排名第 2），省部级二等奖以上 3 项（1 项排名第 1）及国家一级学会科
学技术奖一等奖 1 项（排名第 1）、Scopus“青年科学之星”信息科学领域金奖、
亚洲控制会议最佳论文奖等 6 篇国内外学术会议和机构论文奖。
报告题目：压电陶瓷执行器的智能控制方法
报告人：程龙 中国科学院自动化研究所
程龙简介:
程龙博士，中国科学院自动化研究所研究员，博士生导师，中国科学院大学岗
位教授。目前已发表 SCI 论文 50 余篇，担任 IEEE Trans. Cybernetics、自动化学
报等国内外刊物的编委。入选国家优青、中组部万人计划青年拔尖，中国科学
院卓越青年科学划家计、北京市科技新星计划、国际神经网络学会青年科学家
获。获得 2017 年度国家自然科学二等奖，2015 年中国自动化学会自然科学一等
奖等科技奖励，获得 IEEE 神经网络汇刊的最佳论文奖。
报告题目：航天器自主控制研究进展汇报
报告人：胡庆雷 北京航空航天大学
胡庆雷简介:
胡庆雷，男，1979 年 2 月生，河南省太康县人。现任北京航空航天大学自动化
科学与电气工程学院教授、博士生导师。主要从事飞行器导航、制导与控制等
28
领域应用基础理论与技术的研究，发表科研论文 60 余篇，主持国家自然科学重
点基金项目等多项，获国家技术发明二等奖等多项；担任国际 SCI 检索学术期
刊 IEEE Trans. Aerospace and Electronic Systems 等多个期刊编委。
报告题目：复杂脉冲控制理论及相关应用
报告人：李晓迪 山东师范大学
李晓迪简介:
李晓迪，男，中共党员，数学博士，物理学博士后，教授，博士生导师，山东
省泰山学者青年专家、山东省杰出青年基金获得者、山东省优秀青年基金获得
者、山东省五四青年奖章获得者、山东师范大学数学与统计学院院长、控制与
工程计算研究中心主任。近年来致力于不连续控制系统理论及应用方面的研究，
获得一批应用基础性研究成果。 先后在 IEEE 汇刊、Automatica 等国际权威期刊
发表 SCI收录论文 80 余篇，其中第一作者论文 60 余篇、16 篇入选 ESI前 1%高
被引论文。先后主持国家级科研项目 3 项，省部级等科研项目 7 项。曾先后获
教育部自然科学奖二等奖（2016，排名第一位），第 15 届教育部霍英东青年教
师奖（2015），连续五年入选 Elsevier 中国高被引学者榜（2014-2018），山东省
高等学校优秀科研成果奖一等奖（2015）。目前担任 SCI 期刊 AIMS Mathematics
主编，中国自动化控制理论专业委员会非连续控制学组委员、随机系统控制分
委员会委员。
报告题目：核熵学习理论与方法
报告人：陈霸东 西安交通大学
陈霸东简介:
陈霸东，西安交通大学教授，博导。2008 年毕业于清华大学计算机专业获博士
学位，2010 年 10 月至 2012 年 9 月在美国佛罗里达大学电气与计算机工程系做
博士后研究。研究兴趣包括信号处理、机器学习、人工智能、脑机接口等。发
表学术论文 200 多篇，其中 SCI 收录期刊论文 150 余篇，发表在 IEEE TNNLS,
IEEE TSP, IEEE SPL, AUTOMATICA 等国际著名期刊，8 篇论文获“ESI 高被引论
文”。入选陕西省“百人计划”、陕西省中青年科技创新领军人才、西安交通大学
29
青年拔尖人才（A 类）；获陕西省科学技术奖二等奖、中国自动化学会自然科学
二等奖、陕西省高等学校科学技术奖励一等奖、中国自动化学会青年科学家奖。
陈教授是 IEEE 高级会员，中国认知科学学会理事，国际著名期刊 IEEE TNNLS、
IEEE TCDS编委以及 IEEE 面向信号处理的机器学习(MLSP) 、IEEE 认知与发展
系统(CDS)技术委员会委员。作为项目负责人承担了国家自然科学基金重点和
973 课题等多项重要科研项目。
报告题目：基于主角保持性质的压缩子空间学习
报告人：谷源涛 清华大学
谷源涛，清华大学教授，博导。1998 年毕业于西安交通大学信息与通信工程系
获学士学位，2003 毕业于清华大学电子工程系获博士学位，2012 年至 2013 年
在美国麻省理工学院电气工程与计算机科学系做访问学者。研究兴趣包括信号
处理、无线通信和信息网络等。 2015 年获 IEEE 全球信号与信息处理会议
(GlobalSIP)最佳论文奖，2015 年获 IEEE 国际信号与信息处理会议(ChinaSIP)期
刊论文最佳发表奖。2015 年 2 月起任 IEEE Transactions on Signal Processing 副主
编，2015 年 2 月起任 EURASIP 数字信号处理 handing editor，2017 年 1 月当选
IEEE 信号处理理论与方法技术委员会委员。
报告题目：基于多模态深度学习的脑网络方法与脑疾病辅助诊断
报告人：李阳 北京航空航天大学
李阳简介：
李阳教授、博士生导师，自动化科学与电气工程学院副院长。2008 年 10 月至
2011 年 9 月，在英国谢菲尔德大学获工学博士学位；2012-2013年，在美国北卡
罗来纳大学教堂山分校从事博士后研究工作。2013 年 2 月至今，任北京航空航
天大学“卓越百人”副教授、教授。在计算神经科学、图像处理与深度学习、神
经退行性脑疾病诊断、脑机接口与神经康复等方面开展了具有国际影响的独创
性研究，取得一系列丰硕的研究成果，发表学术论文 50 余篇，其中以第一或通
讯作者在 IEEE Transactions on Neural Networks and Learning Systems, IEEE
Transactions on Medical Imaging 等人工智能及医学图像处理等领域国际权威 SCI
30
期刊上发表论文 36 篇，SCI 他引 400 余次。主持国家自然科学基金联合基金重
点项目、国家自然科学基金面上及青年基金项目、北京市自然科学基金重点/面
上项目及航天合作课题等 10 余项资助。研究成果获得了学术界的高度评价，
2017 年 5 月，与宁波智能产业研究院合作开发的“意念控制转运床”获央视新闻、
新华网等多家媒体正面报道，成功用于宣武、天坛等医院的脑认知康复训练，
实现肢体与神经系统功能重建。应用成果获中国人工智能吴文俊人工智能自然
科学奖（排名第 1），曾获得英国谢菲尔德大学 Harry Worthington 学术奖及中国
优秀自费留学生奖的最高奖励。荣获北京航空航天大学第二十八届“冯如杯”优
秀指导教师奖。现任中国体视学学会理事、《BIOINFO Mechanical Engineering》
主编等。
报告题目：复杂网络迭代学习控制若干问题研究
报告人: 熊文军 西南财经大学
熊文军简介：
熊文军，西南财经大学教授，博士生导师，近些年取得了一系列创新成果并发
表 在 《IEEE Transactions on Automatic Control》、《Automatica》、《IEEE
Transactions on Fuzzy Systems》等国际权威期刊上。其中，在国际控制领域的顶
级期刊《Automatica》上以第一作者身份发表论文一篇，在 IEEE Trans.系列的会
刊上发表论文 9 篇。申请人第一作者发表 SCI 论文 30 余篇。主持了国家自然科
学基金面上项目、国家自然科学基金青年基金、中国博士后面上基金、江苏博
士后面上基金、四川省教育厅重点项目、中央高校基本科研业务费、西南财经
大学引进人才科研启动资助项目、西南石油大学科研启航计划基金等。申报人
2016 年获教育部科技进步一等奖，2015 年论文入选 ESI 高被引，2014 年获四川
省学术和技术带头人后备人选。
31
报告题目：协同学习系统：概念、架构和算法
报告人：郭平 北京师范大学
郭平简介：
郭平, 教授、IEEE 高级会员、CCF 高级会员， IEEE CIS Beijing Chapter 主席
（2015-2016）, 北京师范大学图形图像与模式识别校级实验室主任。曾经在北
京师范大学物理学、北京师范大学和北京理工大学计算机科学与技术、北京师
范大学系统科学等三个一级学科指导博士生。目前在北京师范大学系统分析与
集成学科招收博士生和博士后。他的研究兴趣包括计算智能理论及其在模式识
别、图像处理、软件可靠性工程、天文大数据处理等方面的应用。到目前为止
包括在 IEEE TNN，MNRAS 等期刊和 IJCAI、AAAI、WCCI 等国内外学术会议
上发表论文 360 余篇，获得发明专利 6 项，出版《软件可靠性工程中的计算智
能方法》和《图像语义分析》专著两部，作为第一完成人其研究成果“正则化方
法及其应用”获得 2012 年北京市科学技术三等奖。 郭平教授在北京大学物理学
系光学专业获得硕士学位，在香港中文大学计算机科学与工程学系获得博士学
位。
报告题目：数据驱动优化、建模与应用
报告人：李超杰 哈马德-本-哈里法大学
李超杰简介：
李超杰，博士，皇家墨尔本理工大学研究员。于 2007年，2011年，2017年分别
毕业于重庆大学电子科学与技术本科，计算机科学硕士以及澳大利亚皇家墨尔
本理工大学电力与电子工程博士。鉴于博士期间优秀学术成果，获得国家自费
留学生奖学金。曾就职于皇家墨尔本理工大学工程学院和阿里巴巴国际站从事
算法理论与商业化研究；现就职于 HBKU，主要研究数据科学理论与方法，时
间序列分析与应用，深度神经网络，智能电表数据分析，智能电网优化管理，
分布式优化算法。已发表 SCI 论文约 30 篇，包括 IEEE Trans. SmartGrid, IEEE
Trans. Power System, IEEE Trans. Control Systems Technology等电力与自动化领域
著名杂志，IJCAI，CIKM，ICDM 等人工智能与大数据顶级会议。 2016 年获得
IEEE Power and Energy Society General Meeting 最佳论文。
32
报告题目：复杂噪声情况下的新型卡尔曼滤波器研究
报告人：黄玉龙 哈尔滨工程大学
黄玉龙简介：
黄玉龙，1990年生，2018年12月毕业于哈尔滨工程大学，获工学博士学位。
2016年11月至2017年11月曾赴美国哥伦比亚大学博士联合培养。2018年12月留
校进入哈尔滨工程大学自动化学院工作，破格副教授。曾荣获第十一届中国青
少年科技创新奖、第十三届中国大学生年度人物提名奖、工信创新创业奖学金
特等奖等多项国家级奖励与荣誉，并入选2019年度“香江学者计划”。2019年9月
开始担任美国Mathematical Reviews评论员。黄玉龙长期从事惯性导航、组合导
航和智能信息融合方面的研究工作，在非高斯和自适应状态估计理论方面以及
惯性导航和组合导航应用方面做出了大量的原创性研究工作。至今，已主持国
家自然科学基金青年科学基金项目一项，作为主要人员参与了国家自然科学基
金面上项目2项、总装备部项目1项、海军预研项目1项。在所研究领域以第一作
者或通信作者(第二作者)在国内外重要学术期刊和会议上发表学术论文50余篇，
其中SCI论文30余篇，IEEE Transactions和Automatica国际顶级期刊论文15余篇，
国内顶尖期刊《自动化学报》论文6篇，国际顶级会议论文6篇。担任IEEE
ICCA 2019副编辑，分别在Fusion 2018、ICASSP 2019、IEEE SAM 2020主持了
关于导航和信息融合的专题。
报告题目：基于可变Q梯度的主动噪声控制算法研究
报告人：赵海全 西南交通大学
赵海全简介：
赵海全教授（IEEE 高级会员，美国佛罗里达大学访问学者），博导，1998、
2005 及 2010 年分别于西南交通大学获得学士、硕士及博士学位，先后入选四川
省学术和技术带头人、四川省有突出贡献的优秀专家、四川省杰出青年带头人
以及四川省青年科技创新团队（核心成员），承担国家自然科学基金、省部级
（省杰青、省应用基础重点项目与省带头人资助项目）项目 20 多项，在 IEEE
TIE、IEEE TSP 等国际期刊发表 SCI 论文 130+篇（其中 6 篇 ESI，1 篇热点论
文），授权发明专利 35 项，获中国自动化学会自然科学二等奖、教育部科技进
步二等奖、詹天佑铁道科学技术奖—青年奖以及唐立新优秀学者奖，担任
33
《IEEE Access》期刊副主编(IF:4.098)，以及 AEU- International Journal of
Electronics and Communications (IF:2.15)编委成员。
34
Conference Registration
A conference registration desk will be set up and opened at the Haiyu Hotspring Hotel
(重庆市北碚区海宇温泉酒店), Chongqing from Sept. 27 (13:00) as followings.
Registration Time: Sept. 27, 2019: 13:00-22:00; Sept. 28, 2019: 08:00-22:00.
Registration Address: 1st floor, Haiyu Hotspring Hotel, Beibei District, Chongqing,
China.
Map of Conference Rooms
35
General Information
Haiyu Hotspring Hotel (海宇温泉大酒店) is located at Shuangyuan Road 198, Beibei District, Chongqing. The hotel has a variety of professional services including special luxury rooms, executive lounge, first-class restaurants, coffee bar, international conference center, hot spring spa, fitness center, business center and so on.
Transportation Information
Route 1: (about 1 hour and 10 minutes)
Jiangbei International Airport (江北机场) Yuelai Station (悦来站)
Come out from Exit 1C and walk about 860 meters.
Route 2: (about 1 hour)
Chongqingbei Railway Station (重庆北站) Ranjiaba Station (冉家坝站)
Zhuagyuanbei Station (状元碑)
Come out from Exit 1C and walk about 860 meters.
SurroundingHotels
Beibei direction Line 6 Loop Line
Chongqing library direction
Zhuagyuanbei Station (状元碑) Beibei direction
Line 6
Wangjiazhuang direction Line10
Lijia direction
Line 6 Lijia Station (礼嘉站)
36
Surrounding Hotels
Sheenjoy Hotel (心景酒店)
The hotel is built in the well-known 4A-level scenic spot, Jinyun Mountain. Beside the Jialing River, it covers an area of about 1000 acres with a total construction area of 300,000 square meters. The hotel traces the architectural form of Chongqing Slope Landscaping, which is decorated with water, spring, forest and bamboo. As the first hotel in China with the theme of “bamboo” culture, it uses a large number of natural bamboo series.
Liangjiang Genting Grand Hotel (两江云顶大酒店)
Liangjiang Genting Grand Hotel is located at No. 136 Yunhan Avenue, which is situated at the core of Chongqing Cloud Computing Center, the largest data development and processing center in China. The hotel is 20 kilometers away from the airport, about 20 minutes by car, and only needs 35 minutes to drive from the center of Chongqing’s main city.
Surrounding Restaurants
Haiyu Hotspring Hotel is 960 meters away from Jialing Pedestrian Street which is about 800 meters long and 200 meters wide with a range of Chongqing local foods, such as hot pots.
37
Surrounding Information
Chongqing, referred to as Yu or Ba, is the only municipality directly under the central government, central city, mega city and international metropolis in the mid and west of China. It’s also the center of economic, financial, scientific, shipping and trade logistics in the upper reaches of the Yangtze River. As important strategic pivots for the great development of the western region, Chongqing is an important link between the “one belt and one road” and the Yangtze River economic belt, as well as plays the key role in deepening reform and opening up inland. Chongqing is famous for its mountainous landscape and both Jiangcheng and fog are the main feature.
38
Here are some places worth visiting in Chongqing:
Yangtze River Cableway (长江索道)
Yangtze River Cableway, located in Chongqing, China, is the second cross-river cableway in Chongqing (The first is the Jialing River Cableway (has been demolished)). It has been running for 30 years and is known as “the first air corridor of the Yangtze River” and “mountain city air bus”. The Yangtze River Cableway is a large cross-river passenger ropeway designed and manufactured by China. Its length is 1166 meters. It connects Yuzhong District and Nanan District of Chongqing. It travels between Xinhua Road (Xiaoshizi Station of Rail Transit) in Yuzhong District and Shangxin Street in Nanan District at a speed of 6 meters per second. It takes 4 minutes and has 10,500 passengers per day. Riding on the cableway is the most suitable way to interpret Chongqing’s “three-dimensional traffic” and “mountain city appearance symbols”. When foreign tourists travel to Chongqing, they can fly across the Yangtze River by the cableway and enjoy the famous night scenery of Chongqing in the air, which is a fresh experience. On February 6, 2018, it met the requirements of the national 4A-level tourist scenic spot standard and was approved as a national 4A-level tourist scenic spot.
Transportation: You can take the rail transit line 6 (get on at the Zhuangyuanbei Station, get off at the Xiaoshizi Station).
Crown Escalator (皇冠大扶梯)
Crown Escalator is a junction escalator in Chongqing, connecting the Lianglukou Rail Transit Station and Chongqing Railway Caiyuanba Station, which is one of the characteristic traffic in Chongqing. One-way fare is 2 yuan. The escalator started construction in February 1993 and was completed and operated on February 18, 1996. It is 112 meters long, 1.3 meters wide, 52.7 meters high and 30 degrees inclined, running 0.75 meters per second and taking2 minutes and 30 seconds for the whole operation. It consists of three escalators from the upward and downward ladders and the alternate ladder. Each escalator has a maximum passenger capacity of 13,000 people/hour, making it the second-largest first-class sloping escalator in Asia.
Transportation: You can take the rail transit line 6 (at the Zhuangyuanbei Station, get off at the Hongqihegou Station), then take the rail transit line 3 (get on at the Hongqihegou Station, get off at the Lianglukou Station).
39
Hongyadong (洪崖洞)
The business form of Hongyadong’s “one state, three absolutely, four streets and eight scenes” reflects the Bayu culture and leisure industry. “One state” refers to the cultural and leisure business forms. “Three absolutely” refers to the hanging foot building, the old town of the market town and the Ba culture. “Four streets” refers to the four streets of Hongyadong. “Eight sceneries” refers to the Hongyadong Dicui, the confluence of the two rivers, the hanging feet buildings, the Hongya carvings, the city balcony, the Ba cultural pillar, the riverside delicious street and the Jialing sunset.
Transportation: You can take the rail transit line 6 (get on at the Zhuangyuanbei Station, get off at the Xiaoshizi Station).
Chaotianmen(朝天门)
The beauty of Chaotianmen is always different from that of other sights in Chongqing. Why do you say that? Because of all the beauty of mountain cities, the distant view is always better than the close view. If you want to see Chaotianmen, you can only see it from the other side of the river, Nanbin Road, and if you want to see Nanbin Road, you can only see it from Chaotianmen. You can take a cruise ship from Chaotianmen to visit the Jialing River to Huanghuayuan Bridge, and then turn around to visit to the Yangtze River Bridge, during which the Hongya Cave, Grand Theatre, Science and Technology Museum, Nanbin Road and Sheraton Hotel are all in sight.
Transportation: You can take the rail transit line 6 (get on at the Zhuangyuanbei Station, get off at the Xiaoshizi Station), then walk about 900 meters northeast.
40
Jiefangbei (解放碑)
Jiefangbei is one of the landmark buildings in Chongqing. It is located at the central part of the business district of Yuzhong, Chongqing, at the intersection of Minzu Road, Minquan Road and Zourong Road. The monument is 27.5 meters high and has a spiral staircase to the top. The top of the monument is equipped with clock, direction indicator and wind speed and direction indicator. Jiefangbei was first built in the 29th year of the Republic of China (1940) on the death day of Sun Yat-sen on March 12, and was completed at the end of the 30th year of the Republic of China (1941). It was named “Spiritual Fortress” to inspire the Chinese people to fight hard and win the war. After the victory of the Anti-Japanese War, it was renamed as “The Victory of the Anti-Japanese War”. In 1950, Liu Bochengchanged the title “Chongqing People’s Liberation Monument”. Jiefangbei records the history and culture of Chongqing and supports the past and future of Chongqing. Today, Jiefangbei is synonymous with the Central Business District. It is the core city card of Chongqing and one of the top ten cultural symbols of Chongqing.
Transportation: You can take the rail transit line 6 (get on at the Zhuangyuanbei Station, get off at the Xiaoshizi Station), then walk about 900 meters.
Ciqikou Ancient Town (磁器口古镇)
Ciqikou Ancient Town: National AAAA Grade Scenic Area, the historical and cultural street of Chinese, the protection of traditional street in chongqing, Chongqing “New Twelve Scenes of Bayu”, Bayu’s Folk Culture Tourism–Circle Ciqikou Ancient Town is located on the Jialing River in Shapingba, Chongqing. Built in the Song Dynasty, it has the unique landform of “One River, Two Streams, Three Mountains and Four Streets”, forming a natural harbor, and is an important water and land terminal on the Jialing River. Once were flourishing, Ciqikou Ancient Town is rich in Bayu culture, religious culture, sand magnetic culture, red rock culture and folk culture, each with its own
41
characteristics. A stone road, the Millennium Ciqikou, is the epitome and symbol of the ancient city of Chongqing, and is praised as “Little Chongqing”. Ciqikou Ancient Town has developed traditional performances such as oil extraction, spinning, sugar making, kneading, and Sichuan opera, as well as various traditional snacks and teahouses. The Ciqikou temple fair held every Spring Festival is the most distinctive traditional activity, attracting tens of thousands of citizens to participate.
Transportation: You can take the rail transit line 6 (get on at the Zhuangyuanbei Station, get off at the Xiaoshizi Station), then take the rail transit line 1 (get on at the Xiaoshizi Station, get off at the Ciqikou Station).
42
Index of Authors
-B- Baojun Song SaO II-A Bo Li SaO III-A Bo Zhou SaO III-C B. O. Onasanya SaO III-C Baojie Zhang SaO III-D
-C-
C. L. Philip Chen SaO I-A SaO I-B Chaojie Li SaO II-A Chuandong Li SaO II-B Chenghui Mao SaO II-B Cong Liu SaO II-C Chunyang Zhang SaO III-B Changcheng Xiang SaO III-C Chao Yang SaO III-D
-D-
Daixi Liao SaO I-A Dewen Qiao SaO II-D
-F-
Feng Hu SaO I-B Feng Zhang SaO II-A Fan Yang SaO II-A
-G- Guangyuan Liu SaO I-D Gang Lu SaO II-B Guangyuan Liu SaO III-A
-H- He Ma SaO I-A
Hongjuan Wu SaO I-A Hao Yi SaO I-B Huiyan Zhang SaO I-D Heng Zhang SaO II-A Hongbo Zhang SaO II-A Haoyang Wang SaO II-B He Huang SaO II-B Hongyi Liu SaO III-A Huiyu Nie SaO III-A Huaqing Li SaO III-B Hongyi Li SaO III-B Honggui Han SaO III-B Huiwei Wang SaO III-C
-J- Jinnan Luo SaO I-A Jun Cheng SaO I-A Junxia Liu SaO I-A Jin Qiu SaO I-B Jiajun Yang SaO I-B Jianlei Xu SaO II-C Jiamin Quan SaO III-A Jihai Zhang SaO III-A Jianfeng Li SaO III-A Jie Tan SaO III-A Jinmeng Wang SaO III-B Junfei Qiao SaO III-B Jiaqi Pu SaO III-B Jiajie Lu SaO III-C Jie Zeng SaO III-D Jing Xu SaO III-D
-K-
Kaibo Shi SaO I-A Kaiyue Wang SaO I-C SaO II-A Kun Li SaO I-C Ke Yang SaO II-A
43
Kui Xiong SaO II-D
-L- Lianghao Ji SaO I-B Liangen Yuan SaO I-B Liangliang Li SaO I-C Lu Liu SaO II-B Lianghao Ji SaO II-C Long Chen SaO III-B Liangwei Wang SaO III-C Liangliang Li SaO III-C
-M- Michael Z. Q. Chen SaO I-D Miao Sun SaO II-C Ming Zhan SaO III-D Meng Wang SaO III-D
-N- Nankun Mu SaO II-A SaO II-D
-P- Peichao He SaO I-A Ping Wang SaO I-B Peng Shi SaO I-D Pan Qi SaO II-B
-Q- Qun Liu SaO I-A Qihe Shan SaO I-B Qishuai Wu SaO II-A Qiuyue Wang SaO II-B Qianzhu Wang SaO II-C Qi Zhou SaO III-B
-R-
Ruqi Wang SaO I-A Ruihan Liu SaO I-C Renyi Xie SaO II-B Rui Ding SaO III-C
-S- Shouming Zhong SaO I-A Shihao Xu SaO I-D Shuai Yang SaO I-D Shujie Zhu SaO II-A Xinmiao Dong SaO II-C Shasha Yang SaO II-C Shiyuan Wang SaO II-D Shasha Yan SaO III-C
-T- Tieshan Li SaO I-A SaO I-B Ting Gao SaO I-B Tongkui Yu SaO I-C SaO II-A Tao Dong SaO I-C Tiantian Yu SaO I-C Tiedong Ma SaO I-C Tong Chen SaO III-A Tengteng Zhu SaO III-A Teng Li SaO III-C Tao Peng SaO III-C
-W- Wenqian Xie SaO I-A Wenhong Tian SaO I-A Wei Luo SaO I-B Wenqiang Xu SaO I-B Wei Zhang SaO I-C SaO III-A Wengang Ao SaO I-D Wenhong Liu SaO II-A Wanlu Shi SaO II-A Wei Xue SaO II-A
44
Wanlu Shi SaO II-D Wei Shi SaO II-D Wei Zhang SaO III-A Wenbin Xiao SaO III-B Waihou Ao SaO III-B Wenfeng Hu SaO III-C
-X- Xiang Hu SaO I-A Xiaojie Su SaO I-B Xu Jin SaO I-C Xiangyu Bu SaO I-C Xidong Zhang SaO II-A Xianping Yu SaO II-A Xin Wang SaO II-A Xinqi Huang SaO II-A Xiaojun Zhou SaO II-A Xuchen Wang SaO II-B Xuejun Wang SaO II-B Xing He SaO II-C Xiangguang Dai SaO III-A Xiaoyu Liu SaO III-A Xiaomeng Li SaO III-B XiaolongWu SaO III-B Xiaohong Luo SaO III-D Xinxin Li SaO III-D
-Y- Yuping Zhang SaO I-A Yi Zuo SaO I-A SaO I-B Yuming Feng SaO I-A Yuzhuo Ma SaO I-B Yuming Feng SaO I-C SaO III-A Yun Zou SaO I-D Yongchao Wu SaO I-D Yingsong Li SaO II-A Yuxuan Huang SaO II-B Yingsong Li SaO II-D Yinghua Zhou SaO III-A Yongyi Xiao SaO III-B
Yuan Fan SaO III-C Yuefei Yuan SaO III-C Yi Yang SaO III-C Yi Deng SaO III-D
-Z- Zhengwen Tu SaO I-A Zhengle Zhang SaO I-C Zhengran Cao SaO II-B Zhilong He SaO II-B Zao Fu SaO II-C Zitao Wang SaO III-A Zhaohui Chen SaO III-A Zheng Wang SaO III-B Zhengwen Tu SaO III-C
