i

GENERALIZED PREDICTIVE CONTROL APPROACH FOR A MODIFIED

SINGLE ACTING PNEUMATIC CYLINDER

NU’MAN DIN BIN MUSTAFA

UNIVERSITI TEKNOLOGI MALAYSIA

i

“I hereby declare that I have read this thesis and in my

opinion this thesis is sufficient in terms of scope and quality for the

award of the degree of Master of Engineering (Electrical)”

Signature : ………………………..

Name of Supervisor : IR. DR. AHMAD ‘ATHIF MOHD FAUDZI

Date : 21/9/2014

i

GENERALIZED PREDICTIVE CONTROL APPROACH FOR A MODIFIED

SINGLE ACTING PNEUMATIC CYLINDER

NU’MAN DIN BIN MUSTAFA

A thesis submitted in fulfilment of the

requirements for the award of the degree of

Master of Engineering (Electrical Engineering)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

SEPTEMBER 2014

ii

I declare that this thesis “Generalized Predictive Control Approach for a Modified

Single Acting Pneumatic Cylinder” is the result of my own research except as cited

as in the reference. The thesis has not been accepted for any degree and is not

concurrently submitted in candidature of any other degree.

Signature :……………………………

Name : NU’MAN DIN BIN MUSTAFA

Date : 21/9/2014

iii

Specially dedicated to my beloved family especially

my mother Latifah binti Abu talib for her

endless prayer, encouragement and blessings

iv

ACKNOWLEDGEMENT

I would like to give my sincere appreciation to my dedicated and

hardworking supervisor, Ir. Dr. Ahmad ‘Athif bin Mohd Faudzi for his guidance,

support and endless effort in order to make sure this project finish on time. Without

his reminder, this project would not meet its objectives.

I would also like to give my deepest thanks to my beloved family especially

my mother, Latifah binti Abu talib and my friends for their support and advices.

They play a big role in giving me continuous motivation to finish my study.

I would also want to give my thanks to my colleague that helps and gives idea

for my project especially Mr. Khairuddin Osman, Mohamed Omer, Abdul Rahman

and others. Their knowledge and related work had given me new knowledge and

solutions for my project.

v

ABSTRACT

Pneumatic actuator is a device that converts air pressure to possible motions such as

linear and rotary motion. Although the pneumatic actuator offers many advantages it is

difficult to control. This is due to the nonlinearities involved such as friction and air

compressibility. The equipment used in this research is the Intelligent Pneumatic Actuator

(IPA). Previously, Proportional-Integral (PI) has been used as the controller for the IPA.

Based on the previous result, a controller called generalized predictive controller (GPC) is

proposed. Compared to PI, this controller has the capability to take into account the

nonlinearity factor which is very important in this research. There are two types of GPC

proposed in this research which are GPC with First Order Time Delay (GPC-FOTD) and

GPC with Higher Order (GPC-HO). This research starts with the implementation of PI,

GPC-FOTD and GPC-HO controllers for position and force control in simulations. Then, the

simulation result is validated with the real-time experiments. There are two experiments for

position control, which are position control with and without loads and one experiment for

force control. Then, a Haptic Pneumatic Device (HPD) is developed in order to emulate a

spring by combining the position and force control. By implementing the spring

characteristic to the pneumatic device, a human machine interaction concept is applied to the

device. In summary, GPC-FOTD shows better performance compared to GPC-HO and PI in

terms of stability and better response for position control. For force control the GPC-HO

shows better performance compared to other controllers in terms of tracking and accuracy.

Then for the spring characteristic implementation, response of force versus displacement is

presented where the results show stiffness coefficient (Ks ) is directly proportional to the

output force generated. This device together with GPC controller are capable of giving better

results in terms of spring characteristic emulation control compared to the previous research

on IPA. These results and application hopefully can be used to help people such as in

rehabilitation sector, as exercise equipment and entertainment tools as well as comparison

data for other controller development.

vi

ABSTRAK

Penggerak pneumatik adalah alat yang menukarkan tekanan udara kepada beberapa

gerakan seperti gerakan linear dan berputar. Walaupun penggerak pneumatik menawarkan

banyak kelebihan ia adalah sukar untuk dikawal. Ini adalah disebabkan oleh faktor tak

lelurus yang terlibat seperti geseran dan kemampatan udara. Alat yang digunakan dalam

kajian ini adalah Pneumatik Aktuator Pintar (IPA). Sebelum ini, Proportional-Integral (PI)

telah digunakan sebagai pengawal untuk IPA. Berdasarkan keputusan kajian, pengawal yang

dipanggil Pengawal Ramalan Umum (GPC) dicadangkan sebagai pengawal baru.

Berbanding PI, pengawal ini mempunyai keupayaan untuk mengambil kira faktor tak lelurus

dan ianya adalah penting dalam kajian ini. Terdapat dua jenis GPC yang dicadangkan dalam

kajian ini iaitu GPC dengan Kelewatan Masa Peringkat Pertama (GPC-FOTD) dan GPC

dengan peringkat yang Lebih Tinggi (GPC-HO). Kajian ini bermula dengan pelaksanaan PI,

GPC-FOTD dan pengawal GPC-HO bagi kedudukan dan kuasa kawalan dalam simulasi.

Kemudian, hasil simulasi disahkan dengan eksperimen masa nyata. Terdapat dua eksperimen

untuk kawalan kedudukan, iaitu kawalan kedudukan dengan dan tanpa beban dan satu

eksperimen untuk kawalan daya. Kemudian, satu Alat Haptik Pneumatik (HPD) dihasilkan

untuk menghasilkan satu ciri emulasi spring dengan menggabungkan kawalan kedudukan

dan kuasa. Dengan melaksanakan ciri spring untuk peranti pneumatik, satu konsep interaksi

mesin manusia dapat diadaptasikan ke dalam peranti. Ringkasnya, GPC-FOTD menunjukkan

prestasi yang lebih baik berbanding dengan GPC-HO dan PI dari segi tindak balas yang

stabil dan lebih baik untuk kawalan kedudukan. Untuk kawalan daya GPC-HO menunjukkan

prestasi yang lebih baik berbanding dengan pengawal lain dari segi pengesanan dan

ketepatan. Kemudian untuk pelaksanaan ciri spring, tindak balas tenaga melawan anjakan

dibentangkan. Keputusan menunjukkan pekali pelembut ( Ks ) adalah berkadar langsung

dengan daya keluaran. Peranti ini bersama-sama dengan pengawal GPC mampu memberi

hasil yang lebih baik daripada segi kawalan emulasi ciri spring berbanding dengan

penyelidikan sebelumnya dengan IPA. Keputusan dan aplikasi ini diharapkan boleh

digunakan untuk membantu orang ramai seperti dalam bidang pemulihan, alat latihan dan

alat hiburan serta sebagai data perbandingan untuk pembangunan pengawal yang lain.

vii

TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xiv

LIST OF SYMBOLS xvi

1 INTRODUCTION ............................................................................ 1

1.1 Overview 1

1.2 Problem Statement 2

1.3 Research Objectives 2

1.4 Scope of Work 3

1.5 Thesis Outline 3

2 LITERATURE REVIEW ................................................................ 5

2.1 Introduction 5

2.2 Intelligent Pneumatic Actuator 6

2.3 Generalized Predictive Controller Overview 8

viii

2.4 Position Control 11

2.5 Force and Spring Characteristic 13

2.6 Human Machine Interaction (HMI) Application 16

2.7 Summary 19

3 METHODOLOGY ......................................................................... 20

3.1 Introduction 20

3.2 Pneumatic Actuator Architecture 21

3.2.1 Working operation for pneumatic actuator 22

3.2.2 Pneumatic Actuator Model 24

3.3 Controller Design 26

3.4 Simulation and Experiment 27

3.4.1 Position and Force Simulation 29

3.4.2 Position Control with/without loads 29

3.4.3 Force 30

3.4.4 Spring Characteristic Simulation 31

3.5 Application 32

3.6 Summary 33

4 CONTROLLER APPROACH ...................................................... 35

4.1 GPC algorithm 35

4.1.1 GPC-First order with time delay (FOTD) 35

4.1.2 GPC Algorithm for Higher Order (HO) Model 39

4.1.3 Proportional-Integral (PI) Controller 44

4.2 Controller Implementation 44

4.2.1 GPC-First order with time delay (FOTD) 45

4.2.2 GPC-higher order model (HO) 46

4.2.3 Proportional-integral (PI) controller 48

ix

4.3 Summary 48

5 RESULTS AND DISCUSSIONS ................................................... 49

5.1 Introduction 49

5.2 GPC parameter selection 51

5.3 PWM converter 57

5.4 Position control 58

5.4.1 Simulation and Real-time experiment without load 58

5.4.2 Real time experiment with loads 63

5.5 Force control 67

5.6 Spring function 71

5.7 Haptic Pneumatic Device 75

5.7.1 Control strategies 76

5.8 Summary 77

6 CONCLUSION AND RECOMMENDATION ............................ 78

6.1 Conclusion 78

6.2 Recommendation 79

REFERENCES ..................................................................................................... 80

Appendices A-B ............................................................................................... 87-85

x

LIST OF TABLES

TABLE NO. TITLE PAGE

2.1 Comparison between new and previous cylinder [6, 7] 7

2.2 Details on the improved pneumatic cylinder 7

3.1 Pneumatic cylinder parts [4, 8, 48, 49] 21

5.1 Analysis table for step responses when N2 varied 52

5.2 Analysis table for step responses when Nu is varied 54

5.3 Analysis table for step responses when is varied 55

5.4 Analysis table for step responses when alpha is varied 57

5.5 Analysis table for position control simulation GPC-FOTD

vs. GPC-HO vs. PI 61

5.6 Analysis table for position control real-time experiment

GPC-FOTD vs. GPC-HO 63

5.7 Analysis table for real time experiment position tracking

with horizontal loads 66

5.8 Analysis table for real time experiment position tracking

with vertical loads 67

5.9 Analysis criteria for force control simulation vs.

experiment. 70

5.10 Analysis table for stiffness characteristic implementation 73

xi

LIST OF FIGURES

FIGURE NO. TITLE PAGE

2.1 Literature review flow chart 5

2.2 Intelligent Pneumatic Cylinder developed by [6] 6

2.3 Active 80-faced Polyhedron for Haptic Physical Human-

Machine Interface and an intelligent pneumatic actuator

develop by [7]. 7

2.4 Pneumatic Actuated Seating System (PASS) [4] 8

2.5 Experimental results of compliance control [4] 15

2.6 Concept underlying between human machine interactions

[43]. 17

3.1 Research flow chart 20

3.2 Intelligent Pneumatic Actuator [4] 21

3.3 Pneumatic actuator illustration 23

3.4 Poles and zeros for position transfer function 25

3.5 Poles and zeros for force transfer function 26

3.6 Controller design workflow 26

3.7 Simulation and experiment workflow 28

3.8 Position and Force block diagram 29

3.9 Experiment setup for position control without load 29

3.10 Experiment setup for position control with load (a)

Vertical setup (b) Horizontal setup 30

3.11 Force experiment setup 31

3.12 Damping, spring and mass system [4] 32

3.13 Spring (stiffness) block diagram 32

3.14 Haptic pneumatic device (HPD) design (a) top view, (b)

side view and (c) front view 33

xii

4.1 Reaction Curve Method (RCM) 36

4.2 GPC-FOTD control scheme 45

5.1 Process flow of this chapter 50

5.2 Output response when N2 is varied (a) output (b) control

signal 52

5.3 Step response when Nu is varied (a) output (b) control

signal 53

5.4 Step response when is varied (a) output (b) control

signal 55

5.5 Step response when alpha is varied (a) output (b) control

signal 56

5.6 The signals flow 58

5.7 Simulink block diagram for position control simulation 59

5.8 Simulink block diagram for real-time experiment 59

5.9 Simulation step response for GPC-FOTD vs. GPC-HO vs.

PI 60

5.10 Simulation multistep response for GPC-FOTD vs. GPC-

HO vs. PI 60

5.11 Real-time experiment step response for GPC-FOTD vs.

GPC-HO vs. PI 62

5.12 Real-time experiment multistep response for GPC-FOTD

vs. GPC-HO vs. PI 62

5.13 Step response for real time position control with loads (a)

Horizontal (b) Vertical 64

5.14 Multistep response for real time position control with

loads (a) Horizontal (b) Vertical 65

5.15 Simulink block diagram for force control simulation 68

5.16 Simulink block diagram for force control real time

experiment 68

5.17 Step response comparison for force control simulation

(Sim) vs. experiment (Exp) 69

5.21 Multistep response comparison for force control

simulation (Sim) vs. experiment (Exp) 70

xiii

5.19 Simulation block diagram for stiffness characteristic

implementation 71

5.23 Real-time experiment block diagram for stiffness

characteristic implementation 72

5.21 Stiffness characteristic result for real-time experiment

implementation 73

5.22 Experimental setup for pneumatic actuator stiffness

characteristic analysis 74

5.23 Force vs. Displacement response with different value of Ks 74

5.24 Haptic pneumatic device (HPD) (a) top view, (b) side

view and (c) front view 75

5.25 Control implementation for Pneumatic Device 76

5.26 Haptic pneumatic device (HPD) with human interaction 76

xiv

LIST OF ABBREVIATIONS

HPD - Haptic Pneumatic Device

HMI - Human machine interaction

Ks - Stiffness coefficient

GPC - Generalized Predictive Controller

PSoC - Programmable System on Chip

PI - Proportional-Integral

DAQ - Data Acquisition

PASS - Pneumatic Actuated Seating System

PC - Personal Computer

I2C - Inter-Integrated Circuit

LED - Light-Emitting Diode

DC - Direct Current

PWM - Pulse Width Modulation

MPWM - Modified Pulse Width Modulation

PID - Proportional-Integral-Derivative

SMC - Sliding Mode Controller

MIMO - Multiple Input Multiple Output

ANFIS - Adaptive Neural Fuzzy Inference System

MPC - Model Predictive Controller

MPHC - Model Predictive Heuristic Control

MAC - Model Algorithm Control

DMC - Dynamic Matrix Controller

EHAC - Extended Horizon Adaptive Control

EPSAC - Extended Predictive Control Self Adaptive Control

GMV - Generalized Minimum Variance

MV - Minimum Variance

SCADA - Supervisory Control And Data Acquisition

xv

SISO - Single-input/single-output

ARX - Autoregressive Model with External Input

BTCS - Brake Based Vehicle Traction Control

USM - Ultrasonic Motors

DOF - Degrees Of Freedom

PHI - Pneumatically Driven Haptic Interface

ARMAX - Autoregressive Moving Average with Exogenous Inputs

FOTD - First order with time delay

CARIMA - Controller Auto-Regressive Integrated Moving Average

HO - Higher Order model

IAE - Integral Absolute Error

ISE - Integral Square Error

xvi

LIST OF SYMBOLS

y - Prediction output of the system

y - System output

w - Reference set point

{}E - Prediction set

u - Control signal

1N - Minimum prediction horizon

2N - Maximum prediction horizon

uN - Control horizon

- Weighting factor

- Weighting factor

F - Generated output force

sK - Stiffness coefficient

x - Displacement.

Fd - Driving force,

F - Applied force,

Ff - Frictional force,

m - Mass of the piston

x - Acceleration

A1 , A2 - Corresponding cross sectional area in chamber 1 and 2

d - Dead time

sT - Sampling time

ba, - Parameter for FOTD model.

1t - The time when the output reaches 28.3% of its steady state value

2t - The time when the output reaches 63.2% of its steady state value

A, B - The polynomial for different backward shift operator

xvii

n - An integer,

)(tx - Disturbance.

)(te - Zero mean white noise,

C - Noise polynomial

- An adjustable value that influence the dynamic response of the system

Kp, - Tuning parameters.

Ki - Tuning parameters.

Kd - Tuning parameters.

TR - Rise time

%OS - Percentage of overshoot

%eSS. - Percentage of steady state error

C_s - Control signal for PWM conversion

TS - Settling time

1

CHAPTER 1

1 INTRODUCTION

1.1 Overview

Pneumatic is a device that used air pressure as it power source. It converts the

air pressure into a possible motion such as linear and rotary. Pneumatic actuator have

been largely used in the industries and also actively used for research purpose. This

is due to the advantages that the pneumatic actuator offers such as high power-to-

weight ratio, relatively low cost, easy to maintain, lighter, and have simple structure

compare to other actuators that available in the market [1]. In addition, the pneumatic

actuator also is an environmental friendly device because it used air [2]. Example of

pneumatic application such as to position controls applied in robotic manipulator,

loading/unloading systems, air balance systems and gripper. Despite of all the

advantages compared to electrical actuator used in robot and machines, it is difficult

to control. This is due to the nonlinear factor involved such as the nonlinearity of the

valve, compressibility of air and friction [3]. Therefore, many researchers put their

effort in order to make the pneumatic actuator controllable for position and force

control by proposing complex controller, new control strategies and etc. [3].

Pandian et. al [2] proved that air motor can be used as an alternative for

electric powered motor. Although it is difficult to control pneumatic motor compared

to electric motor, with certain control approach a better results can be achieved in

terms of high accuracy, low steady state error and fast response.

2

Pneumatic actuator can be divided into two categories which are piston type

and rotary type. Both of this actuator type uses air pressure as its power source. From

the historical development, the development of the pneumatic actuator were created

since the 16th

century [4]. Since then, there are many developments regarding the

pneumatic actuator in order to suit different automation, industry and applications.

Now at the 20th

century, the pneumatic actuator has evolved with complex and better

sensors. For example [4] develop an intelligent pneumatic actuator with combination

of different micro precision sensors and valve. This later on was applied to an

application called Pneumatic Actuator Seating System [4]. The same actuator from

the research will be used in this research however with different controller algorithm

and methodology.

1.2 Problem Statement

1. The pneumatic actuator is difficult to control due to the nonlinear factor

involved [3].

2. Although result from the previous work is good with ability to do tracking

and fast response, further improvement can be done such as low transient

response, higher accuracy and better tracking [4].

1.3 Research Objectives

The objectives of this research are:

1. To design a Generalized Predictive Controller (GPC) for pneumatic cylinder

position and force control.

3

2. To compare the GPC controller for position control and force control

performance with existing PI (Proportional-Integral) controller in simulation

and real time experiment.

1.4 Scope of Work

The scopes of this research are as below:

1. The controller development is using MATLAB-Simulink as the platform.

2. The optimization of the GPC controller will be based on trial and error and

past knowledge of the plant. Although the optimization is based on trial and

error, certain guideline is follow which will be explained in Chapter 3 section

3.4.1.

3. The controller performance will be based on ISE and IAE. Lower ISE and

IAE will resulted in good control performance in terms of lower cumulative

error.

1.5 Thesis Outline

Chapter one is discussing about the thesis overview, problem statements,

research objectives and scopes of this research. Then, chapter two present the

literature review regarding the intelligent pneumatic development, GPC history,

position control, force and Spring characteristic and lastly about human machine

interaction. Chapter 3 is discussing about the research methodology used in this

research from the start until the results meet the objective requirement. Next is

chapter 4, which is the controller approach. In this chapter, the GPC derivation PI

controllers are discussed. Chapter 5 is the results and discussions. In this chapter, the

4

research results for position and force control is presented. In addition, the device

designed for spring characteristic implementation is also presented. Lastly, is chapter

six which is the conclusion and recommendation. In this chapter, the thesis

conclusion which reflected the thesis objective is presented. Meanwhile, for further

improvement suggestion is presented in the recommendation.

.

80

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