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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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