NEW SYSTEM IDENTIFICATION MODEL FOR PREDICTIVE FUNCTIONAL

CONTROL WITH OBSERVER FOR AN INTELLIGENT PNEUMATIC ACTUATOR

KHAIRUDDIN BIN OSMAN

UNIVERSITI TEKNOLOGI MALAYSIA

© Universiti Teknikal Malaysia Melaka

UNIVERSITI TEKNOLOGI MALAYSIA PSZ 19: 16 (Pind. 1 /07)

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Author's full name : KHAIRUDDIN BIN OSMAN

Date of birth _: 3_0_J_U_L Y_ l 9--'8'-l ___ ____________ _

Title : NEW SYSTEM IDENTIFICATION MODEL FOR PREDICTIVE FUNCTIONAL CONTROL WITH OBSERVER FOR AN INTELLIGENT PNEUMATIC ACTUATOR

Academic Session : 2014/2015 - 2 ---------------------

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810730086243 IR. DR. AHMAD 'ATHIF BIN MOHD FAUDZI

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Date : 30 MARCH 2015 Date: 30 MARCH 2015

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© Universiti Teknikal Malaysia Melaka

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Philosophy (Electrical Engineering)"

Signature

Name of Supervisor I : Ir. Dr. Ahmad 'Athifbin Mohd Faudzi

Date 30 March 2015

' ,, -~

Signature --·---··--·------················-··--·-···---·--··--··--···

Name of Supervisor II: Prof. Dr. Mohd Fua'ad bin Rahmat

Date 3 0 March 2015

© Universiti Teknikal Malaysia Melaka

BAHAGIAN A - Pengesahan Kerjasama*

Adalah disahkan bahawa projek penyelidikan tesis ini telah dilaksanakan melalui kerjasama

antara _ _________ dengan _________ _

Disahkan oleh:

Tandatangan

Nama

Jawatan (Cop rasmi)

Tarikh :

* Jika penyediaan tesis/projek melibatkan kerjasama.

BAHAGIAN B - Untuk Kegunaan Pejabat Sekolah Pengajian Siswazah

Tesis ini telah diperiksa dan diakui oleh:

N ama dan Alamat Pemeriksa Luar

Nama dan Alamat Pemeriksa Dalam

Prof. Dr. Mohd Nasir Taib

Faculty Electrical Engineering,

Universiti Teknologi Mara (UiTM),

40450 Shah Alam,

Selangor.

Prof. Madya Dr. Yahaya bin Md Sam

Fakulti Kejuruteraan Elektrik,

UTM Johor Bahru.

Disahkan oleh Timbalan Pendaftar di Sekolah Pengajian Siswazah:

Tandatangan : Tarikh :

Nama ASRAM BIN SULAIMAN @ SAIM

© Universiti Teknikal Malaysia Melaka

NEW SYSTEM IDENTIFICATION MODEL FOR PREDICTIVE FUNCTIONAL

CONTROL WITH OBSERVER FOR AN INTELLIGENT PNEUMATIC ACTUATOR

KHAIRUDDIN BIN OSMAN

A thesis submitted in fulfilment of the

requirements for the award of the degree of

Doctor of Philosophy (Electrical Engineering)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

MARCH2015

© Universiti Teknikal Malaysia Melaka

11

I declare that this thesis entitled "New System Identification Model for Predictive

Functional Control with Observer for an Intelligent Pneumatic Actuator" is the result of

my own research except as cited in the references. The thesis has not been accepted for

any degree and is not concurrently submitted in candidature of any other degree.

Signature

Name

Date

: Khairuddin bin Osman

: 30 March 2015

© Universiti Teknikal Malaysia Melaka

iii

Specially dedicated to:

My kind parents for their priceless support and motivation.

iv

ACKNOWLEDGEMENT

Praise to the Almighty...

First of all, thanks to our Creator for the continuous blessing and for giving me

the strength and chances in completing this thesis.

Special thanks to my project supervisor, Ir. Dr. Ahmad ‘Athif bin Mohd Faudzi

and co-supervisor, Prof. Dr. Mohd Fua’ad bin Rahmat, for their guidance, support and

helpful comments in doing this research.

My family deserves special mention for their constant support and for their role

of being the driving force towards the success of my project. My sincere appreciation

also goes to everyone whom I may not have mentioned above who have helped directly

or indirectly in the completion of my PhD thesis.

I would also like to thank Universiti Teknologi Malaysia (UTM), Ministry of

Education (MOE) Malaysia under Skim Latihan Akademik IPTA (SLAI), Universiti

Teknikal Malaysia Melaka (UTeM) and Okayama University for their support. Thanks

to them.

v

ABSTRACT

This thesis presents System Identification (SI) model development and controller

design using Predictive Functional Control with Observer (PFC-O) algorithm for real-

time control of Intelligent Pneumatic Actuator (IPA). An application of Ankle-Foot

Rehabilitation Exerciser (AFRE) device uses the IPA system. The plant mathematical

model in discrete transfer functions was approximated using the MATLAB system

identification toolbox for open-loop input-output experimental data. The SI process was

conducted through a series of activities including observation and data gathering, Auto

Regressive with Exogenous Input (ARX) model structure selection, model estimation,

model validation and the implementation of PFC-O algorithm designed to prove the

operation of IPA is acceptable. PFC-O algorithm was selected as a new control strategy

for IPA to overcome the real-time nonlinearities and uncertain characteristics. PFC-O

algorithm was used for position control, force control and realized compliance control

for stiffness characteristic through MODBUS communication protocol. Performance

assessment of the controller was programmed into MATLAB and validated through two

real-time experiments: Personal Computer (PC) based (using National Instrument (NI)

devices) and embedded based (using Programmable System on Chip (PSoC)

microcontroller). The results between simulation, theoretical calculation and both real-

time experiment matched closely and achieved the control objectives. Towards the

AFRE application, the IPA can be configured through MATLAB Graphical User

Interface (GUI) via personal computer where user can adjust the required Range of

Motion (ROM) and resistance in real-time. The AFRE system testing was conducted

successfully on selected subjects for various ROM and resistance using the proposed

algorithm. The significant finding demonstrates that the new PFC-O control algorithm

reduces the control effort and gives better performance in terms of tracking accuracy as

compared to the existing control algorithm.

vi

ABSTRAK

Tesis ini membentangkan pembangunan model Pengenalpastian Sistem (SI) dan

reka bentuk Kawalan Fungsian Ramalan dengan Pemerhati (PFC-O) algoritma untuk

kawalan masa nyata Penggerak Pneumatik Pintar (IPA). Aplikasi peranti Senaman

Pemulihan Buku Lali-Kaki (AFRE) menggunakan sistem IPA itu. Model matematika

dalam rangkap pindah diskret telah dianggarkan menggunakan kotak alat

pengenalpastian sistem MATLAB untuk gelung-buka masukan-keluaran data

eksperimen. Proses SI telah dijalankan melalui satu siri aktiviti termasuk pemerhatian

dan perhimpunan data, pemilihan struktur model Auto Regresif bersama Input Luaran

(ARX), penganggaran model, pengesahan model dan implimentasi PFC-O algoritma

direka untuk membuktikan operasi IPA boleh diterima. PFC-O algoritma dipilih sebagai

strategi kawalan baru untuk IPA bagi mengatasi parameter tak lelurus masa sebenar dan

ciri-ciri yang tidak menentu. PFC-O algoritma digunakan untuk kawalan kedudukan,

kawalan kuasa dan sifat kawalan kelembutan direalisasikan melalui protokol komunikasi

MODBUS. Penilaian prestasi pengawal diprogramkan ke MATLAB dan disahkan

melalui dua ujikaji masa nyata: berdasarkan Komputer Peribadi (PC) (dengan

menggunakan peranti Instrumen Nasional (NI)) dan berdasarkan terbenam

(menggunakan mikropengawal Sistem Atur Cara pada Cip (PSoC)). Keputusan antara

simulasi, pengiraan teori dan ujikaji kedua-dua masa nyata dipadankan dan mencapai

objektif kawalan. Bagi mencapai aplikasi AFRE, IPA boleh dikonfigurasikan menerusi

grafik Antara Muka Pengguna (GUI) MATLAB melalui komputer peribadi di mana

pengguna boleh menyesuaikan Julat Pergerakan (ROM) yang diperlukan dan rintangan

dalam masa nyata. Ujian sistem AFRE yang telah dijalankan ke atas subjek yang dipilih

untuk pelbagai ROM dan rintangan berjaya menggunakan algoritma yang dicadangkan.

Penemuan penting menunjukkan kawalan algoritma PFC-O baru dapat mengurangkan

usaha kawalan dan memberikan prestasi yang lebih baik dari segi ketepatan pengesanan

berbanding dengan pengawal algoritma sedia ada.

vii

TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLE xi

LIST OF FIGURES xii

LIST OF ABBREVIATIONS xv

LIST OF SYMBOLS xvii

LIST OF APPENDICES xix

1 INTRODUCTION 1

1.1 Research Background 1

1.2 Problem Statement 4

1.3 Research Objectives 5

1.4 Scope of Work 5

1.5 Contribution of the Work 6

1.6 Organization of the Thesis 6

2 LITERATURE REVIEW 8

2.1 Introduction 8

2.2 Pneumatic Cylinders 8

viii

2.3 System Identification and Controller

Selection 15

2.4 Ankle Rehabilitation and its Associated

Challenges 21

2.5 Summary 26

3 RESEARCH METHODOLOGY 27

3.1 Introduction 27

3.2 Research Process Flow 27

3.3 Summary 30

4 MODEL AND CONTROL ALGORITHM

STRATEGIES 31

4.1 Introduction 31

4.2 Intelligent Pneumatic Actuator (IPA) System

Operations 31

4.3 System Identification Technique 34

4.3.1 Position Model 37

4.3.2 Force Model 39

4.4 Predictive Functional Control with Observer

(PFC-O) Design 42

4.4.1 Predictive Functional Control (PFC) 42

4.4.2 Observer 46

4.5 Stiffness Characteristic 48

4.6 Embedded Controller Algorithm with Stiffness

Characteristics 50

4.6.1 Simplification of Algorithm 50

4.6.2 Control Stability Test 54

4.6.3 Profiling Algorithm Execution

Performance 55

4.7 Summary 58

ix

5 INTELLIGENT PNEUMATIC ACTUATOR

SYSTEM ANALYSIS 59

5.1 Introduction 59

5.2 Experimental Setup 59

5.3 IPA System Experiments 64

5.3.1 Models Tracking Analysis 64

5.3.2 Stiffness Characteristics with Deflection

Analysis 65

5.3.3 Position Control with Loading Effects

Analysis 66

5.4 Model Validations 67

5.4.1 Position Control 68

5.4.2 Force Control 71

5.5 Embedded System Validations 75

5.5.1 Stiffness Characteristics with Deflection

Analysis 75

5.5.2 Position Control with Loading Effect

Analysis 78

5.6 Summary 87

6 ANKLE-FOOT REHABILITATION EXERCISER

SYSTEM 88

6.1 Introduction 88

6.2 Design and Development of AFRE 89

6.2.1 Characteristics 89

6.2.2 Prototype 90

6.2.3 MODBUS Communication Protocol 93

6.2.4 Graphical User Interface (GUI) 98

6.3 AFRE System Experiments 99

6.3.1 Testing with Measurement Tool 99

6.3.2 Testing with Selected Subjects 100

x

6.3.2.1 Fixed Movement 101

6.3.2.1 Two-way movement 102

6.4 Data Collection for AFRE System 103

6.4.1 Testing with Measurement Tool 103

6.4.2 Testing with Selected Subject 104

6.4.2.1 Fixed movement 104

6.4.2.2 Two-way movement 105

6.5 Summary 109

7 CONCLUSIONS AND FUTURE WORKS 110

7.1 Conclusions 110

7.2 Suggestions for Future Works 111

REFERENCES 113

Appendices A – C 124 – 132

xi

LIST OF TABLE

TABLE NO. TITLE PAGE

4.1 Valve Configuration 32

5.1 Comparison of the simulated performances for position

control 69

5.2 Comparison of simulated and experimental

performance for position control using PFC-O 71

5.3 Comparison of the simulated performances for force

control 73

5.4 Comparison of simulated and experimental performance

for force control using PFC-O 74

5.5 Comparison of deflection results 77

5.6 Comparison of horizontal payloads for

experimental PFC-O performances 81

5.7 Comparison of vertical payloads for experimental PFC-O

performances 84

6.1 Comparison of the subject’s profile 101

xii

LIST OF FIGURES

FIGURE NO. TITLE PAGE

2.1 IPA system and its parts 14

2.2 Ankle rehabilitation trends 26

3.1 Model development flow chart 28

4.1 IPA schematic operations 33

4.2 Process model for SI and its implementation 35

4.3 Response of system to step input signal 38

4.4 Position Model views 39

4.5 Response of system to PRBS signal 40

4.6 Force Model views 41

4.7 Block diagram of PFC-O for plant model 48

4.8 Coil Spring illustration 49

4.9 Block diagram for control system with stiffness

characteristic 50

4.10 PFC controller stage 51

4.11 Observer stage 53

4.12 Eigenvalues of the closed-loop control system 55

4.13 PSoC CY8C27243 56

4.14 Measurement of effective algorithm execution time 57

4.15 Measurement of effective algorithm sampling time 58

5.1 National Instrument (NI) devices connection 60

5.2 Test panel monitoring 61

xiii

5.3 New wiring instruction to SCB-68 M series devices

terminal 62

5.4 Embedded system communication 63

5.5 Real experiment setup using NI devices 65

5.6 Pneumatic actuator with mass 66

5.7 Loading effect experimental setup 67

5.8 Simulation step responses for position 68

5.9 Simulation multi-step responses for position 69

5.10 Position step responses 70

5.11 Position multi-step responses 70

5.12 Simulation step responses for force 72

5.13 Simulation multi-step responses for force 72

5.14 Force step responses 73

5.15 Force multi-step responses 74

5.16 Stiffness characteristic responses 76

5.17 Position step response for different stiffness 76

5.18 Deflection analysis responses 77

5.19 Experimental position step response for PFC-O under

horizontal loads 79

5.20 Experimental position multi-step response for PFC-O

under horizontal loads 80

5.21 Experimental position step response for PFC-O under

vertical loads 82

5.22 Experimental position multi-step response for PFC-O

under vertical loads 83

5.23 PFC-O force outputs during positional multi-step

experiment under horizontal loads 85

5.24 PFC-O force outputs during positional multi-step

experiment under vertical loads 86

6.1 Movements of the ankle-foot (Dai et al., 2011) 89

xiv

6.2 Position foot and angle movement of dorsiflexion-plantar

flexion (Ortega et al., 2012) 90

6.3 AFRE system design with dimension using SolidWorks 91

6.4 Real AFRE system and its part 91

6.5 Top level function 94

6.6 Turn on IPA control algorithm (servomechanism on) 95

6.7 Write set point to IPA (position, stiffness) 96

6.8 Flow Chart 4 - Read feedback data from IPA

(position, pressure) 97

6.9 AFRE GUI 99

6.10 Validation with measurement tool 100

6.11 Real physical picture for each subject 101

6.12 Comparison of data embedded and measurement

responses 103

6.13 Fixed movement results 105

6.14 Two-way movement result for subject 1 106

6.15 Two-way movement result for subject 2 107

6.16 Two-way movement result for subject 3 108

6.17 Summary of maximum performance of the subjects 109

xv

LIST OF ABBREVIATIONS

IPA - Intelligent Pneumatic Actuator

PASS - Pneumatic Actuator Seating System

PI - Proportional-Integral

SI - System Identification

PFC-O - Predictive Functional Control with observer

NI - National Instrument

PSoC - Programmable System on Chip

CPM - Continuous Passive Motion

ROM - - Minimum Range of Motion

GUI - Graphical User Interface

HME - Human Muscle Enhancer

ISAC - Intelligent Soft Arm Control

MP - Myo-Pneumatic

PLC - Programmable Logic Controller

ADC - Analog to Digital Converter

PC - Personal Computer

USB - Universal Serial Bus

CAD - Computer Aided Design

CAM - Computer Aided Manufacturing

PRSD - Planetary Roller Spindle Drive

LED - Light Emitting Diode

PRBS - Pseudo Random Binary Sequence

PAM - Pneumatic Artificial Muscle

ARX - Auto-Regressive with Exogenous Input

xvi

MGA - Modified Genetic Algorithm

MRE - Mixed-Reality Environment

RLS - Recursive Least Squares

ARMA - Auto-Regressive Moving-Average

PID - Proportional-Integral-Derivative

MPC - Model Predictive Control

DMC - Dynamic Matrix Control

MAC - Model Algorithm Control

GPC - Generalized Predictive Control

EPVA - Electro-Pneumatic Valve Actuator

CARMA - Controlled Auto-Regressive Moving Average

DOF - Degrees of Freedoms

ROM - Range of Motion

PPAFO - Powered Portable Devices Ankle-Foot Orthosis

KAFO - Knee Ankle Foot Orthosis

DAQ - Data Acquisition

ARMAX - Auto-Regressive Moving Average with Exogenous

Input

OE - Output-Error

BJ - Box-Jenkins

FPE - Final Prediction Error

MLS - Maximum Length Sequence

PWM - Pulse-Width Modulation

AIC - Akaike's Information Criteria

PSO - Particle Swarm Optimization

I2C - Inter-Integrated Circuit

UART - Universal Asynchronous Receiver/Transmitter

Sim - Simulation

Emb - Embedded

xvii

LIST OF SYMBOLS

Fd - force data

P1, P2 - pressure data

A1, A2 - cross-sectional areas

d - time delay

na - number of poles

nb - number of zeros

V - loss function,

na - number of approximated parameter,

N - number of sample

y - true value

y - approximate value

y - mean value

Δt - bit interval or clock pulse time

xk - the state model

uk - the input model

yk - the measured output model

i - value of n

yk - the most recent measured output

Ψ - time constant

F - force reference

ks - coefficient of stiffness

n1 - one coincidence horizon

Kob - gain observer

δ - deflection

xviii

W - the force exerted on a body by gravity

g - gravitational acceleration

np - PSoC 11-bit delta-sigma

x', y' - the mobile coordinate system

OS - Overshoot

TS - Settling Time

TR - Rise Time

ess - Steady State Error

IAE - Integral Absolute Error

xix

LIST OF APPENDICES

APPENDIX TITLE PAGE

A List of Publications 124

B List of Awards 130

C Calculation 131

1

CHAPTER 1

INTRODUCTION

1.1 Research Background

Actuators that can process information from an input given and control the

output independently are highly demanded in applications of mechatronics. Pneumatic

actuating system is normally chosen because of their advantages of high power-to-

weight ratio, lightweight, comparative low cost, easy maintenance and having a simple

structure. Moreover, pneumatic actuators are safe and reliable. They are relatively small

in size compared to hydraulic actuators. They have fast response, and at high

temperatures and in nuclear environments, they have the added advantages over

hydraulic actuators. Pneumatic systems have many attributes that make them attractive

for use in difficult environments: gases are not subjected to the temperature limitations

of hydraulic fluids; the actuator exhaust gases need not be collected, so fluid return lines

are unnecessary and long term storage is not a problem because pneumatic systems are

virtually dry and have no organic materials.

Pneumatic systems were first created in the 16th century. Since then, many

developments have been done to the pneumatic actuators to suit the different automation

and industrial purposes according to the desired accuracy and performance and to the

amount of force that is needed for each particular application. In the 20th century,

complex and intelligent pneumatic systems have been developed. The intelligent

pneumatic plant used in this research was taken from previous researches by