New system identification model for predictive functional control with observer for an intelligent pneumatic actuator.
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
DECLARATION OF THESIS
PSZ 19: 16 (Pind. 1/07)
I UNDERGRADUATE PROJECT PAPER AND COPYRIGHT
Author's full name
: KHAIRUDDIN BIN OSMAN
Date of birth
_:3_0_J_U_LY
_ 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
-- - - - - - -- - - - - - -- - ---
I declare that this thesis is classified as :
D
CONFIDENTIAL
(Contains confidential information under the Official Secret
Act 1972)*
D
RESTRICTED
(Contains restricted information as specified by the
organisation where research was done)*
Q
OPEN ACCESS
I agree that my thesis to be published as online open access
(full text)
I acknowledged that Universiti Teknologi Malaysia reserves the right as follows :
1.
2.
3.
The thesis is the property of Universiti Teknologi Malaysia.
The Library of Universiti Teknologi Malaysia has the right to make copies for the purpose
of research only.
The Library has the right to make copies of the thesis for academic exchange .
SIGNATURE
810730086243
NOTES
IR. DR. AHMAD 'ATHIF BIN MOHD FAUDZI
(NEW IC NO./PASSPORT NO.)
NAME OF SUPERVISOR
Date : 30 MARCH 2015
Date: 30 MARCH 2015
*
If the thesis is CONFIDENTIAL or RESTRICTED, please attach with the letter from
theorganisation with period and reasons for confidentiality or restriction.
© Universiti Teknikal Malaysia Melaka
"We hereby declare that we have read this thesis and in our opinion this thesis is
sufficient in terms of scope and quality for the award of the degree of Doctor of
Philosophy (Electrical Engineering)"
Signature
Name of Supervisor I : Ir. Dr. Ahmad 'Athifbin Mohd Faudzi
Date
30 March 2015
Ｍｾ＠
' ,,
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
Tarikh :
Nama
Jawatan
(Cop rasmi)
* Jika p eny ediaan 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
Prof. Dr. Mohd Nasir Taib
Faculty Electrical Engineering,
Universiti Teknologi Mara (UiTM),
40450 Shah Alam,
Selangor.
Nama dan Alamat Pemeriksa Dalam
Prof. Madya Dr. Yahaya bin Md Sam
Fakulti Kejuruteraan Elektrik,
UTM Johor Bahru.
Disahkan oleh Timbalan Pendaftar di Sekolah Pengajian Siswazah:
Tandatangan :
Nama
Tarikh :
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
: Khairuddin bin Osman
Date
: 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 realtime 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 realtime 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
pengenalpastian
pindah
sistem
diskret
MATLAB
telah
dianggarkan
untuk
menggunakan
gelung-buka
kotak
alat
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
1
2
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
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
LITERATURE REVIEW
8
2.1
Introduction
8
2.2
Pneumatic Cylinders
8
viii
2.3
System Identification and Controller
Selection
2.4
2.5
3
4
15
Ankle Rehabilitation and its Associated
Challenges
21
Summary
26
RESEARCH METHODOLOGY
27
3.1
Introduction
27
3.2
Research Process Flow
27
3.3
Summary
30
MODEL AND CONTROL ALGORITHM
STRATEGIES
31
4.1
Introduction
31
4.2
Intelligent Pneumatic Actuator (IPA) System
4.3
4.4
Operations
31
System Identification Technique
34
4.3.1
Position Model
37
4.3.2
Force Model
39
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
4.7
Summary
55
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
5.3.3
Position Control with Loading Effects
Analysis
5.4
5.5
67
5.4.1
Position Control
68
5.4.2
Force Control
71
Embedded System Validations
5.5.2
75
Stiffness Characteristics with Deflection
Analysis
6
66
Model Validations
5.5.1
5.6
65
75
Position Control with Loading Effect
Analysis
78
Summary
87
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
6.4
6.5
7
6.3.2.1 Fixed Movement
101
6.3.2.1 Two-way movement
102
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
Summary
109
CONCLUSIONS AND FUTURE WORKS
110
7.1
Conclusions
110
7.2
Suggestions for Future Works
111
REFERENCES
Appendices A – C
113
124 – 132
xi
LIST OF TABLE
TABLE NO.
TITLE
4.1
Valve Configuration
5.1
Comparison of the simulated performances for position
control
5.2
69
71
Comparison of the simulated performances for force
control
5.4
32
Comparison of simulated and experimental
performance for position control using PFC-O
5.3
PAGE
73
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
5.7
6.1
81
Comparison of vertical payloads for experimental PFC-O
performances
84
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
5.20
Experimental position multi-step response for PFC-O
under horizontal loads
5.21
6.1
83
PFC-O force outputs during positional multi-step
experiment under horizontal loads
5.24
82
Experimental position multi-step response for PFC-O
under vertical loads
5.23
80
Experimental position step response for PFC-O under
vertical loads
5.22
79
85
PFC-O force outputs during positional multi-step
experiment under vertical loads
86
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
ˆ
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-toweight 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
CONTROL WITH OBSERVER FOR AN INTELLIGENT PNEUMATIC ACTUATOR
KHAIRUDDIN BIN OSMAN
UNIVERSITI TEKNOLOGI MALAYSIA
© Universiti Teknikal Malaysia Melaka
UNIVERSITI TEKNOLOGI MALAYSIA
DECLARATION OF THESIS
PSZ 19: 16 (Pind. 1/07)
I UNDERGRADUATE PROJECT PAPER AND COPYRIGHT
Author's full name
: KHAIRUDDIN BIN OSMAN
Date of birth
_:3_0_J_U_LY
_ 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
-- - - - - - -- - - - - - -- - ---
I declare that this thesis is classified as :
D
CONFIDENTIAL
(Contains confidential information under the Official Secret
Act 1972)*
D
RESTRICTED
(Contains restricted information as specified by the
organisation where research was done)*
Q
OPEN ACCESS
I agree that my thesis to be published as online open access
(full text)
I acknowledged that Universiti Teknologi Malaysia reserves the right as follows :
1.
2.
3.
The thesis is the property of Universiti Teknologi Malaysia.
The Library of Universiti Teknologi Malaysia has the right to make copies for the purpose
of research only.
The Library has the right to make copies of the thesis for academic exchange .
SIGNATURE
810730086243
NOTES
IR. DR. AHMAD 'ATHIF BIN MOHD FAUDZI
(NEW IC NO./PASSPORT NO.)
NAME OF SUPERVISOR
Date : 30 MARCH 2015
Date: 30 MARCH 2015
*
If the thesis is CONFIDENTIAL or RESTRICTED, please attach with the letter from
theorganisation with period and reasons for confidentiality or restriction.
© Universiti Teknikal Malaysia Melaka
"We hereby declare that we have read this thesis and in our opinion this thesis is
sufficient in terms of scope and quality for the award of the degree of Doctor of
Philosophy (Electrical Engineering)"
Signature
Name of Supervisor I : Ir. Dr. Ahmad 'Athifbin Mohd Faudzi
Date
30 March 2015
Ｍｾ＠
' ,,
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
Tarikh :
Nama
Jawatan
(Cop rasmi)
* Jika p eny ediaan 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
Prof. Dr. Mohd Nasir Taib
Faculty Electrical Engineering,
Universiti Teknologi Mara (UiTM),
40450 Shah Alam,
Selangor.
Nama dan Alamat Pemeriksa Dalam
Prof. Madya Dr. Yahaya bin Md Sam
Fakulti Kejuruteraan Elektrik,
UTM Johor Bahru.
Disahkan oleh Timbalan Pendaftar di Sekolah Pengajian Siswazah:
Tandatangan :
Nama
Tarikh :
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
: Khairuddin bin Osman
Date
: 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 realtime 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 realtime 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
pengenalpastian
pindah
sistem
diskret
MATLAB
telah
dianggarkan
untuk
menggunakan
gelung-buka
kotak
alat
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
1
2
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
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
LITERATURE REVIEW
8
2.1
Introduction
8
2.2
Pneumatic Cylinders
8
viii
2.3
System Identification and Controller
Selection
2.4
2.5
3
4
15
Ankle Rehabilitation and its Associated
Challenges
21
Summary
26
RESEARCH METHODOLOGY
27
3.1
Introduction
27
3.2
Research Process Flow
27
3.3
Summary
30
MODEL AND CONTROL ALGORITHM
STRATEGIES
31
4.1
Introduction
31
4.2
Intelligent Pneumatic Actuator (IPA) System
4.3
4.4
Operations
31
System Identification Technique
34
4.3.1
Position Model
37
4.3.2
Force Model
39
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
4.7
Summary
55
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
5.3.3
Position Control with Loading Effects
Analysis
5.4
5.5
67
5.4.1
Position Control
68
5.4.2
Force Control
71
Embedded System Validations
5.5.2
75
Stiffness Characteristics with Deflection
Analysis
6
66
Model Validations
5.5.1
5.6
65
75
Position Control with Loading Effect
Analysis
78
Summary
87
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
6.4
6.5
7
6.3.2.1 Fixed Movement
101
6.3.2.1 Two-way movement
102
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
Summary
109
CONCLUSIONS AND FUTURE WORKS
110
7.1
Conclusions
110
7.2
Suggestions for Future Works
111
REFERENCES
Appendices A – C
113
124 – 132
xi
LIST OF TABLE
TABLE NO.
TITLE
4.1
Valve Configuration
5.1
Comparison of the simulated performances for position
control
5.2
69
71
Comparison of the simulated performances for force
control
5.4
32
Comparison of simulated and experimental
performance for position control using PFC-O
5.3
PAGE
73
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
5.7
6.1
81
Comparison of vertical payloads for experimental PFC-O
performances
84
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
5.20
Experimental position multi-step response for PFC-O
under horizontal loads
5.21
6.1
83
PFC-O force outputs during positional multi-step
experiment under horizontal loads
5.24
82
Experimental position multi-step response for PFC-O
under vertical loads
5.23
80
Experimental position step response for PFC-O under
vertical loads
5.22
79
85
PFC-O force outputs during positional multi-step
experiment under vertical loads
86
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
ˆ
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-toweight 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