Comparison Linear And Nonlinear Model For Fuzzy Logic Controller Design Of A Cruise Control System.
ii
“I hereby declare that this report is the result of my own work except for quotes as cited
in the references”
Signature
: ____________________________
Author
: SITI JULIANA BT ABU BAKAR
Date
:
iii
“I hereby declare that I have read this report and in my opinion this report is sufficient in
terms of the scope and quality for the award of Bachelor of Electronic Engineering
(Industrial Electronics) With Honours”
Signature
: ___________________
Supervisor’s Name
: MR. KHAIRUDDIN BIN OTHMAN
Date
:
iv
Dedicated to my beloved mother and father
v
ACKNOWLEDGEMENT
First of all, I would like to take this opportunity to express my utmost and sincere
gratitude to my supervisor, En. Khairuddin Bin Osman. He has proved himself to be an
excellent and devoted supervisor with his kindness and patience. He has given me
important advices, and aspiration, and guided me throughout the whole project. Thank
you for all help and guide.
Secondly, I would also like to thank my beloved parents and my family. They
have given me the greatest moral support that I ever had when I was feeling down. On the
other hand, I would like to show my appreciation to all the lecturers who have taught me
over the years in UTeM. They have taught me invaluable knowledge which is essential in
completing this project. Most importantly, the knowledge acquired has prepared me for
my career in future.
Furthermore, I would like to thank my friends and course mates for sharing their
knowledge with me. Thank you for the encouragement and help. All of you have been
very kind, caring and I will always treasure our friendships.
vi
ABSTRACT
Automobile cruise control system is a system that maintains the speed of a car
regardless whether it is moving on a flat road, uphill or downhill without stepping onto
acceleration or brake pedals. The speed has to be maintained at a desired value and it can
be achieved by controlling the speed of the car. Therefore, fuzzy logic controller was
designed to control linear and nonlinear cruise control system to produce a desired
performance. This project also demonstrates the comparison between linear and nonlinear
model of cruise control system and lastly, the implementation will carried out using GUI
programming.
vii
ABSTRAK
Kawalan kelajuan kereta merupakan sistem yang mengekalkan kelajuan kereta
sepanjang perjalanan sama ada bergerak di atas jalan yang rata, mendaki bukit atau
menuruni bukit tanpa menekan pedal minyak dan brek sepanjang masa dan secara
berterusan. Pengekalan kelajuan kereta boleh dicapai dengan mengawal kelajuan
berdasarkan halaju yang dikehendaki. Oleh itu pengawal diperlukan untuk mencapai
matlamat ini. Dalam projek ini pengawal logik kabur digunakan dengan menetukan
kedudukan kutub bagi persamaan ciri gelung tutup untuk mendapatkan keluaran atau
hasil yang dikehendaki. Di dalam projek ini juga akan membincangkan perbezaan antara
model linear dan model tidak linear sistem kelajuan kereta dan akhir sekali perlaksaan
antara muka pengguna akan digunakan untuk memaparkan perbaezaan di antara dua
model ini dengan jelas.
viii
TABLE OF CONTENTS
CHAPTER
I
CONTENTS
PAGES
TITLE
i
DECLARATION
ii
DEDICATION
iv
ACKNOWLEDGEMENT
v
ABSTRACT
vi
ABSTRAK
vii
TABLE OF CONTENTS
viii
LIST OF TABLES
xii
LIST OF FIGURES
xiii
LIST OF ABBREVATIONS
xv
INTRODUCTION
1.0
Introduction
1
1.1
Objective
2
1.2
Scope
2
1.3
Problem Statement
3
1.4
Project methodology
3
1.4.1
3
1.5
Process Flow Chart
Thesis Outline
6
ix
II
LITERATURE REVIEW
2.0
Introduction
8
2.1
Cruise Control System
8
2.2
Introduction to How Cruise Control System Work
10
2.3
Conventional Cruise Control
11
2.4
Component for cruise control system
12
2.5
III
2.4.1
Vehicle’s Speed Sensor
12
2.4.2
Cruise Control Module
13
2.4.3
Actuator
13
2.4.4
Brake Switch
13
2.4.5
Clutch Switch
14
2.4.6
Throttle Linkage
14
Physical system of a cruise control system
14
MODELING OF CRUISE CONTROL SYSTEM
3.0
Introduction
18
3.1
Deriving the Block Diagram
18
3.2
Value of Parameter and Constant
22
3.3
Transfer Function of the Model
22
3.3.1
Determination of State-Variables
23
3.3.2
State and Output Equations
23
3.3.3
The Transfer Function
24
Linearization of the Transfer Function
25
3.4.1
26
3.4
3.5
Approximation of Time Delay
Derivation of nonlinear cruise control plant
28
x
IV
DESIGN OF CONTROLLER
4.0
Introduction
31
4.1
Fuzzy logic controller
31
4.2
Choosing Fuzzy Logic Controller Inputs and Output
33
4.3
Putting Control Knowledge into Rule-Base
Linguistic Descriptions for Linear Model
4.3.1
Fuzzy Quantification of Knowledge for
Linear Model Cruise Control
4.3.2
38
Putting Control Knowledge into Rule-Bases
Linguistic Descriptions for Nonlinear Model
4.4.1
4.4.2
38
Fuzzy Quantification of Knowledge for
Nonlinear Model Cruise Control
42
Design Nonlinear model Fuzzy Logic Controller
Using MATLAB
V
36
Design Linear model Fuzzy Logic Controller
Using MATLAB
4.4
34
43
4.5
Design Criteria for the Desired Performance
44
4.6
Graphical User Interface (GUI)
44
4.6.1
Introduction of GUI
44
4.6.2
How a Graphical User Interface works
45
4.6.3
How to build User Interface in MATLAB 7.0
45
RESULT, ANALYSIS AND DISCUSSION
5.0
Introduction
47
5.1
Result for Linear System
47
5.1.1
SIMULINK Block Diagram for linear
System without Fuzzy logic controller
47
xi
5.1.2
Step Response of Linear System without
Fuzzy logic Controller
5.1.3
SIMULINK Block Diagram for linear system
With Fuzzy logic controller
5.1.4
5.2
Step Response of Linear System with
50
Results for Nonlinear System
52
Step Response of Nonlinear System with
Fuzzy Logic Controller
5.4
VI
49
Fuzzy logic controller
5.2.1
5.3
48
53
Analysis and comparison between Linear and
Nonlinear model of a cruise control system
55
Result for GUI system
57
CONCLUSION AND RECOMMENDATION
6.0
Introduction
60
6.1
Conclusion
60
6.2
Recommendation
61
REFERENCES
62
APPENDIX A
64
APPENDIX B
76
xii
LIST OF TABLES
TABLE NO.
TITLE
PAGES
3.1
Physical Values for the System
22
4.1
Rule table for Cruise Control
35
4.2
Rule table for nonlinear cruise control system
41
5.1
Response for linear model
51
5.2
Response for nonlinear model
54
5.3
Comparison of output response for linear and
Nonlinear model
56
xiii
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE S
1.1
Process Flow Chart
4
2.1
Cruise control system in automobile
9
2.2
Power button on the steering.
11
2.3
A moving car modeled as a cart traveling on a float road
15
2.4
A moving car modeled as a cart traveling uphill
16
2.5
A moving car modeled as a cart traveling downhill
17
3.1
A general block diagram representing the model of
a car in motion
20
3.2
A block diagram by Lewis and Yang (1997)
21
3.3
A general block diagram representing the nonlinear
model of a car
28
3.4
Equation in DEE block for nonlinear system
30
4.1
Fuzzy controller architecture
32
4.2
Human Controlling for Cruise Control system cart
33
4.3
Fuzzy Controller for Cruise Control System Cart
33
4.4
FIS editor for linear model cruise control
36
4.5
Membership Function for input variable “error”
36
4.6
Membership Function for input variable “derror”
37
4.7
Membership Function for output variable “output1”
37
4.8
Block Diagram for Linear cruise control system
4.9
with Fuzzy Logic controller
38
Membership function for input variable “error”
42
xiv
4.10
Membership function for input variable “derror”
42
4.11
Membership function for output variable “output1”
43
4.12
Block diagram for linear cruise control system
with fuzzy logic controller
5.1
Linear system of cruise control system without
Fuzzy Logic controller
5.2
50
Nonlinear system of cruise control system with
Fuzzy Logic controller
5.6
50
Step response of velocity linear system with
Fuzzy Logic controller
5.5
49
Linear system of cruise control system with
Fuzzy Logic controller
5.4
48
Step response of velocity linear system without
Fuzzy Logic controller
5.3
43
52
Step response of velocity nonlinear system with
Fuzzy Logic controller
54
5.7
Output Response for linear model
55
5.8
Output Response for nonlinear model
55
5.9
Graphic User Interface for Linear Model
58
5.10
Graphic User Interface for Nonlinear Model
59
xv
LIST OF ABBREVIATION
F
nett
- Nett force
Ca - Coefficient of the air-drag force
C - coefficient of the engine
1
F - Drive Force
d
refv - Output speed
wv - Wind gust
v - Speed
u - Throttle angle
θ - Grading of road
F - Gravitational force
g
F - Air-drag force
a
1
CHAPTER 1
INTRODUCTION
1.0
Introduction
Fuzzy logic was first proposed by Lotfi A. Zadeh of the University of
California at Berkeley in a 1965 paper. He elaborated on his ideas in a 1973 paper
that introduced the concept of "linguistic variables", which in this article equates to a
variable defined as a fuzzy set. Fuzzy logic controller is most popular now in logic
design controller because it easy to understand and uses rules and reasoning principle
similar to the way humans think.
Most real life physical systems are actually non- linear systems. Conventional
design approaches use different approximation methods to handle non-linearity. A
linear approximation technique is relatively simple, however it tends to limit control
performance and may be costly to implement in certain applications. A piecewise
linear technique works better, although it is tedious to implement because it often
requires the design of several linear controllers. A lookup table technique may help
improve control performance, but it is difficult to debug and tune. Furthermore in
complex systems where multiple inputs exist, a lookup table may be impractical or
very costly to implement due to its large memory requirements. Fuzzy logic provides
an alternative
2
solution to non- linear control because it is closer to the real world. Non-linearity is
handled by rules, membership functions, and the inference process which results in
improved performance, simpler implementation, and reduced design costs
In this project, the linear and nonlinear model of intelligent cruise control
system was design using fuzzy logic controller for the result to improves the high
stability system and gives better performance. Other important thing, this project will
demonstrate the comparison between linear and nonlinear model for artificial
intelligent (fuzzy logic controller) design of cruise control system. The most
common characteristic to be compared are steady state error, percentage overshoot
and the settling time in order to identify a good response of the controller.
1.1
Objective
The main objective of this project is to perform and show how a fuzzy
controller is tunable comparison between linear and nonlinear model for fuzzy logic
controller design of a cruise control system. Secondly is to develop a linear and
nonlinear system for fuzzy logic controller design of a cruise control system by using
Graphic User Interface (GUI). The purpose of the GUI is to allow user to view the
performance of the cruise control system clearly.
1.2
Scope
The implementation of this project is mainly on software programming.
Performance of these controllers with linear and nonlinear models will be compared
and analyzed by using MATLAB and GUI programming.
3
Works also begin with a derivation of a suitable mathematical model of a
linear and nonlinear cruise control system.
Next is to analyze the response of the system using fuzzy controller and
lastly, simulation will be carried out using Matlab and GUI interface and a
comparative assessment of the impact of each model will be compared and analyzed
1.3
Proble m State ment
The problem of cruise control system is to maintain the output speed of the
system as set by the input signal. For example, if a driver desires to maintain the car
speed at 30 kilometer per hour, then the system should be able to produce the desired
output even when the vehicle traveling downhill and uphill. Other problems
encountered by the fuzzy logic controller are: (1) extracting a model from fuzzy logic
system is difficult. (2) Fuzzy system requires finer tuning before they are operational.
(3) Difficult to get mathematically precise linear and nonlinear models for the cruise
control system using Matlab.
1.4
Project Methodology
1.4.1
Process Flow Chart
Figure 1.1 shown the flow chart for the comparison linear and nonlinear
model for fuzzy logic controller design of a cruise control system. For the
implementation of this project, there are several development of research project
needs to be considered:
4
Figure 1.1: Process Flow Chart
Methodology approach for this project development is state as below:
1)
Gathering information
Firstly, figure out the project title, try to understand it and perform feasibility
study based on references books and journal on the cruise control system for linear
and nonlinear model and fuzzy logic controller. Then, the project title, scope and
objectives are confirmed.
5
2)
System Analysis
Analysis will be done when the mathematic equation for both model of cruise
control system was derived. Information from the references books and internet
sources are gathered to support the validity of the analysis process. Try to understand
how both linear and nonlinear of a cruise control system work in real life.
3)
Simulation studies & review
Lots of time will be spent in practicing programming skills by using
MATLAB 7.0 on how to implement and design a fuzzy logic controller for both
cruise control system models. Note that, higher performance of proposed fuzzy
controller for both model adaptive cruise control systems is expected by tuning the
width and center point of membership functions and scaling factor. The tuning by
evolutionary computation, such as genetic algorithms, is expected as future works.
4)
Design & development
The linear and nonlinear model of a cruise control system was fully design
and implemented using fuzzy logic controller in MATLAB and GUI. The purpose of
the GUI is to allow user to view a performance of the cruise control system clearly.
5)
Verification & comparison
At this stage, a complete system is ready and it will show the comparison
between linear and nonlinear model for cruise control system. The verification phase
will ensure that the designed model meet the primary objectives.
6
6)
Further improvement
After verification and testing complete, the program should meet the primary
objectives set earlier in the duration of the project, which both linear and nonlinear
model can achieve a steady state output. Any errors that occur through the system
will be solved.
1.5
Thesis Outline
The first chapter of this thesis will include the background of the project,
objective of this project need to achieve at the end of this project. Another, this
chapter also will briefly explain the scope of the project, problem statement,
methodology approach and thesis outline.
Chapter 2 will focuses on cruise control system in detail. Another, this
chapter also discusses how the cruise control system works in both linear and
nonlinear model related, conventional cruise control system and lastly it explains the
component of cruise control system and a physical system of a cruise control system.
Chapter 3 will explain the modeling of cruise control system which starts
with the derivation of mathematic modeling for cruise control system. The
background study regarding mathematic modeling of a cruise control system was
carried out from the general block diagram of a car in motion. Another important
thing, the study also covered on the block diagram indicates precise components of
the forces, the engine transfer function and the other important properties of the
block diagram that was thoroughly discussed before.
Chapter 4 will describe on how to model a cruise control system using Fuzzy
Logic controller. This chapter also discusses the characteristic and the basic elements
in the Fuzzy Logic Controller.
7
Lastly, chapter 5 will carry out cover on the result of the linear and nonlinear
model of a cruise control system from the SIMULINK block diagram in MATLAB.
The analysis of the linear and nonlinear model of a cruise control system will cover
in term of percent overshoot, peak time, settling time, and percent steady state error.
Other than that, the GUI system is also discussed on this section. The discussion will
focus on the detail of step response for linear system with and without the fuzzy logic
controller, the step response for the nonlinear system, and lastly the GUI
implementation on the system.
8
CHAPTER 2
LITERATURE REVIEW
2.0
Introduction
The following discussion mainly focuses on cruise control system in detail.
Another, this chapter also discusses how the cruise control system works in both
linear and nonlinear model related, conventional cruise control system and lastly it
explains the component of cruise control system and a physical system of a cruise
control system.
2.1
Cruise Control System
What is the cruise control system? The cruise control system to regulate the
vehicle speed, so that it follows the driver’s command and maintain the speed at the
commanded level [3]. Other idea is, automobile's cruise control, which is a device
designed to maintain a constant vehicle speed. The output variable of the system is
vehicle speed. The input variable is the engine's torque output, which is regulated by
the throttle [9].
Engine and
other automobile systems are
increasingly
controlled
electronically. This has led to improved fuel economy, reduced pollution, improved
driving safety and
“I hereby declare that this report is the result of my own work except for quotes as cited
in the references”
Signature
: ____________________________
Author
: SITI JULIANA BT ABU BAKAR
Date
:
iii
“I hereby declare that I have read this report and in my opinion this report is sufficient in
terms of the scope and quality for the award of Bachelor of Electronic Engineering
(Industrial Electronics) With Honours”
Signature
: ___________________
Supervisor’s Name
: MR. KHAIRUDDIN BIN OTHMAN
Date
:
iv
Dedicated to my beloved mother and father
v
ACKNOWLEDGEMENT
First of all, I would like to take this opportunity to express my utmost and sincere
gratitude to my supervisor, En. Khairuddin Bin Osman. He has proved himself to be an
excellent and devoted supervisor with his kindness and patience. He has given me
important advices, and aspiration, and guided me throughout the whole project. Thank
you for all help and guide.
Secondly, I would also like to thank my beloved parents and my family. They
have given me the greatest moral support that I ever had when I was feeling down. On the
other hand, I would like to show my appreciation to all the lecturers who have taught me
over the years in UTeM. They have taught me invaluable knowledge which is essential in
completing this project. Most importantly, the knowledge acquired has prepared me for
my career in future.
Furthermore, I would like to thank my friends and course mates for sharing their
knowledge with me. Thank you for the encouragement and help. All of you have been
very kind, caring and I will always treasure our friendships.
vi
ABSTRACT
Automobile cruise control system is a system that maintains the speed of a car
regardless whether it is moving on a flat road, uphill or downhill without stepping onto
acceleration or brake pedals. The speed has to be maintained at a desired value and it can
be achieved by controlling the speed of the car. Therefore, fuzzy logic controller was
designed to control linear and nonlinear cruise control system to produce a desired
performance. This project also demonstrates the comparison between linear and nonlinear
model of cruise control system and lastly, the implementation will carried out using GUI
programming.
vii
ABSTRAK
Kawalan kelajuan kereta merupakan sistem yang mengekalkan kelajuan kereta
sepanjang perjalanan sama ada bergerak di atas jalan yang rata, mendaki bukit atau
menuruni bukit tanpa menekan pedal minyak dan brek sepanjang masa dan secara
berterusan. Pengekalan kelajuan kereta boleh dicapai dengan mengawal kelajuan
berdasarkan halaju yang dikehendaki. Oleh itu pengawal diperlukan untuk mencapai
matlamat ini. Dalam projek ini pengawal logik kabur digunakan dengan menetukan
kedudukan kutub bagi persamaan ciri gelung tutup untuk mendapatkan keluaran atau
hasil yang dikehendaki. Di dalam projek ini juga akan membincangkan perbezaan antara
model linear dan model tidak linear sistem kelajuan kereta dan akhir sekali perlaksaan
antara muka pengguna akan digunakan untuk memaparkan perbaezaan di antara dua
model ini dengan jelas.
viii
TABLE OF CONTENTS
CHAPTER
I
CONTENTS
PAGES
TITLE
i
DECLARATION
ii
DEDICATION
iv
ACKNOWLEDGEMENT
v
ABSTRACT
vi
ABSTRAK
vii
TABLE OF CONTENTS
viii
LIST OF TABLES
xii
LIST OF FIGURES
xiii
LIST OF ABBREVATIONS
xv
INTRODUCTION
1.0
Introduction
1
1.1
Objective
2
1.2
Scope
2
1.3
Problem Statement
3
1.4
Project methodology
3
1.4.1
3
1.5
Process Flow Chart
Thesis Outline
6
ix
II
LITERATURE REVIEW
2.0
Introduction
8
2.1
Cruise Control System
8
2.2
Introduction to How Cruise Control System Work
10
2.3
Conventional Cruise Control
11
2.4
Component for cruise control system
12
2.5
III
2.4.1
Vehicle’s Speed Sensor
12
2.4.2
Cruise Control Module
13
2.4.3
Actuator
13
2.4.4
Brake Switch
13
2.4.5
Clutch Switch
14
2.4.6
Throttle Linkage
14
Physical system of a cruise control system
14
MODELING OF CRUISE CONTROL SYSTEM
3.0
Introduction
18
3.1
Deriving the Block Diagram
18
3.2
Value of Parameter and Constant
22
3.3
Transfer Function of the Model
22
3.3.1
Determination of State-Variables
23
3.3.2
State and Output Equations
23
3.3.3
The Transfer Function
24
Linearization of the Transfer Function
25
3.4.1
26
3.4
3.5
Approximation of Time Delay
Derivation of nonlinear cruise control plant
28
x
IV
DESIGN OF CONTROLLER
4.0
Introduction
31
4.1
Fuzzy logic controller
31
4.2
Choosing Fuzzy Logic Controller Inputs and Output
33
4.3
Putting Control Knowledge into Rule-Base
Linguistic Descriptions for Linear Model
4.3.1
Fuzzy Quantification of Knowledge for
Linear Model Cruise Control
4.3.2
38
Putting Control Knowledge into Rule-Bases
Linguistic Descriptions for Nonlinear Model
4.4.1
4.4.2
38
Fuzzy Quantification of Knowledge for
Nonlinear Model Cruise Control
42
Design Nonlinear model Fuzzy Logic Controller
Using MATLAB
V
36
Design Linear model Fuzzy Logic Controller
Using MATLAB
4.4
34
43
4.5
Design Criteria for the Desired Performance
44
4.6
Graphical User Interface (GUI)
44
4.6.1
Introduction of GUI
44
4.6.2
How a Graphical User Interface works
45
4.6.3
How to build User Interface in MATLAB 7.0
45
RESULT, ANALYSIS AND DISCUSSION
5.0
Introduction
47
5.1
Result for Linear System
47
5.1.1
SIMULINK Block Diagram for linear
System without Fuzzy logic controller
47
xi
5.1.2
Step Response of Linear System without
Fuzzy logic Controller
5.1.3
SIMULINK Block Diagram for linear system
With Fuzzy logic controller
5.1.4
5.2
Step Response of Linear System with
50
Results for Nonlinear System
52
Step Response of Nonlinear System with
Fuzzy Logic Controller
5.4
VI
49
Fuzzy logic controller
5.2.1
5.3
48
53
Analysis and comparison between Linear and
Nonlinear model of a cruise control system
55
Result for GUI system
57
CONCLUSION AND RECOMMENDATION
6.0
Introduction
60
6.1
Conclusion
60
6.2
Recommendation
61
REFERENCES
62
APPENDIX A
64
APPENDIX B
76
xii
LIST OF TABLES
TABLE NO.
TITLE
PAGES
3.1
Physical Values for the System
22
4.1
Rule table for Cruise Control
35
4.2
Rule table for nonlinear cruise control system
41
5.1
Response for linear model
51
5.2
Response for nonlinear model
54
5.3
Comparison of output response for linear and
Nonlinear model
56
xiii
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE S
1.1
Process Flow Chart
4
2.1
Cruise control system in automobile
9
2.2
Power button on the steering.
11
2.3
A moving car modeled as a cart traveling on a float road
15
2.4
A moving car modeled as a cart traveling uphill
16
2.5
A moving car modeled as a cart traveling downhill
17
3.1
A general block diagram representing the model of
a car in motion
20
3.2
A block diagram by Lewis and Yang (1997)
21
3.3
A general block diagram representing the nonlinear
model of a car
28
3.4
Equation in DEE block for nonlinear system
30
4.1
Fuzzy controller architecture
32
4.2
Human Controlling for Cruise Control system cart
33
4.3
Fuzzy Controller for Cruise Control System Cart
33
4.4
FIS editor for linear model cruise control
36
4.5
Membership Function for input variable “error”
36
4.6
Membership Function for input variable “derror”
37
4.7
Membership Function for output variable “output1”
37
4.8
Block Diagram for Linear cruise control system
4.9
with Fuzzy Logic controller
38
Membership function for input variable “error”
42
xiv
4.10
Membership function for input variable “derror”
42
4.11
Membership function for output variable “output1”
43
4.12
Block diagram for linear cruise control system
with fuzzy logic controller
5.1
Linear system of cruise control system without
Fuzzy Logic controller
5.2
50
Nonlinear system of cruise control system with
Fuzzy Logic controller
5.6
50
Step response of velocity linear system with
Fuzzy Logic controller
5.5
49
Linear system of cruise control system with
Fuzzy Logic controller
5.4
48
Step response of velocity linear system without
Fuzzy Logic controller
5.3
43
52
Step response of velocity nonlinear system with
Fuzzy Logic controller
54
5.7
Output Response for linear model
55
5.8
Output Response for nonlinear model
55
5.9
Graphic User Interface for Linear Model
58
5.10
Graphic User Interface for Nonlinear Model
59
xv
LIST OF ABBREVIATION
F
nett
- Nett force
Ca - Coefficient of the air-drag force
C - coefficient of the engine
1
F - Drive Force
d
refv - Output speed
wv - Wind gust
v - Speed
u - Throttle angle
θ - Grading of road
F - Gravitational force
g
F - Air-drag force
a
1
CHAPTER 1
INTRODUCTION
1.0
Introduction
Fuzzy logic was first proposed by Lotfi A. Zadeh of the University of
California at Berkeley in a 1965 paper. He elaborated on his ideas in a 1973 paper
that introduced the concept of "linguistic variables", which in this article equates to a
variable defined as a fuzzy set. Fuzzy logic controller is most popular now in logic
design controller because it easy to understand and uses rules and reasoning principle
similar to the way humans think.
Most real life physical systems are actually non- linear systems. Conventional
design approaches use different approximation methods to handle non-linearity. A
linear approximation technique is relatively simple, however it tends to limit control
performance and may be costly to implement in certain applications. A piecewise
linear technique works better, although it is tedious to implement because it often
requires the design of several linear controllers. A lookup table technique may help
improve control performance, but it is difficult to debug and tune. Furthermore in
complex systems where multiple inputs exist, a lookup table may be impractical or
very costly to implement due to its large memory requirements. Fuzzy logic provides
an alternative
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solution to non- linear control because it is closer to the real world. Non-linearity is
handled by rules, membership functions, and the inference process which results in
improved performance, simpler implementation, and reduced design costs
In this project, the linear and nonlinear model of intelligent cruise control
system was design using fuzzy logic controller for the result to improves the high
stability system and gives better performance. Other important thing, this project will
demonstrate the comparison between linear and nonlinear model for artificial
intelligent (fuzzy logic controller) design of cruise control system. The most
common characteristic to be compared are steady state error, percentage overshoot
and the settling time in order to identify a good response of the controller.
1.1
Objective
The main objective of this project is to perform and show how a fuzzy
controller is tunable comparison between linear and nonlinear model for fuzzy logic
controller design of a cruise control system. Secondly is to develop a linear and
nonlinear system for fuzzy logic controller design of a cruise control system by using
Graphic User Interface (GUI). The purpose of the GUI is to allow user to view the
performance of the cruise control system clearly.
1.2
Scope
The implementation of this project is mainly on software programming.
Performance of these controllers with linear and nonlinear models will be compared
and analyzed by using MATLAB and GUI programming.
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Works also begin with a derivation of a suitable mathematical model of a
linear and nonlinear cruise control system.
Next is to analyze the response of the system using fuzzy controller and
lastly, simulation will be carried out using Matlab and GUI interface and a
comparative assessment of the impact of each model will be compared and analyzed
1.3
Proble m State ment
The problem of cruise control system is to maintain the output speed of the
system as set by the input signal. For example, if a driver desires to maintain the car
speed at 30 kilometer per hour, then the system should be able to produce the desired
output even when the vehicle traveling downhill and uphill. Other problems
encountered by the fuzzy logic controller are: (1) extracting a model from fuzzy logic
system is difficult. (2) Fuzzy system requires finer tuning before they are operational.
(3) Difficult to get mathematically precise linear and nonlinear models for the cruise
control system using Matlab.
1.4
Project Methodology
1.4.1
Process Flow Chart
Figure 1.1 shown the flow chart for the comparison linear and nonlinear
model for fuzzy logic controller design of a cruise control system. For the
implementation of this project, there are several development of research project
needs to be considered:
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Figure 1.1: Process Flow Chart
Methodology approach for this project development is state as below:
1)
Gathering information
Firstly, figure out the project title, try to understand it and perform feasibility
study based on references books and journal on the cruise control system for linear
and nonlinear model and fuzzy logic controller. Then, the project title, scope and
objectives are confirmed.
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2)
System Analysis
Analysis will be done when the mathematic equation for both model of cruise
control system was derived. Information from the references books and internet
sources are gathered to support the validity of the analysis process. Try to understand
how both linear and nonlinear of a cruise control system work in real life.
3)
Simulation studies & review
Lots of time will be spent in practicing programming skills by using
MATLAB 7.0 on how to implement and design a fuzzy logic controller for both
cruise control system models. Note that, higher performance of proposed fuzzy
controller for both model adaptive cruise control systems is expected by tuning the
width and center point of membership functions and scaling factor. The tuning by
evolutionary computation, such as genetic algorithms, is expected as future works.
4)
Design & development
The linear and nonlinear model of a cruise control system was fully design
and implemented using fuzzy logic controller in MATLAB and GUI. The purpose of
the GUI is to allow user to view a performance of the cruise control system clearly.
5)
Verification & comparison
At this stage, a complete system is ready and it will show the comparison
between linear and nonlinear model for cruise control system. The verification phase
will ensure that the designed model meet the primary objectives.
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6)
Further improvement
After verification and testing complete, the program should meet the primary
objectives set earlier in the duration of the project, which both linear and nonlinear
model can achieve a steady state output. Any errors that occur through the system
will be solved.
1.5
Thesis Outline
The first chapter of this thesis will include the background of the project,
objective of this project need to achieve at the end of this project. Another, this
chapter also will briefly explain the scope of the project, problem statement,
methodology approach and thesis outline.
Chapter 2 will focuses on cruise control system in detail. Another, this
chapter also discusses how the cruise control system works in both linear and
nonlinear model related, conventional cruise control system and lastly it explains the
component of cruise control system and a physical system of a cruise control system.
Chapter 3 will explain the modeling of cruise control system which starts
with the derivation of mathematic modeling for cruise control system. The
background study regarding mathematic modeling of a cruise control system was
carried out from the general block diagram of a car in motion. Another important
thing, the study also covered on the block diagram indicates precise components of
the forces, the engine transfer function and the other important properties of the
block diagram that was thoroughly discussed before.
Chapter 4 will describe on how to model a cruise control system using Fuzzy
Logic controller. This chapter also discusses the characteristic and the basic elements
in the Fuzzy Logic Controller.
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Lastly, chapter 5 will carry out cover on the result of the linear and nonlinear
model of a cruise control system from the SIMULINK block diagram in MATLAB.
The analysis of the linear and nonlinear model of a cruise control system will cover
in term of percent overshoot, peak time, settling time, and percent steady state error.
Other than that, the GUI system is also discussed on this section. The discussion will
focus on the detail of step response for linear system with and without the fuzzy logic
controller, the step response for the nonlinear system, and lastly the GUI
implementation on the system.
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CHAPTER 2
LITERATURE REVIEW
2.0
Introduction
The following discussion mainly focuses on cruise control system in detail.
Another, this chapter also discusses how the cruise control system works in both
linear and nonlinear model related, conventional cruise control system and lastly it
explains the component of cruise control system and a physical system of a cruise
control system.
2.1
Cruise Control System
What is the cruise control system? The cruise control system to regulate the
vehicle speed, so that it follows the driver’s command and maintain the speed at the
commanded level [3]. Other idea is, automobile's cruise control, which is a device
designed to maintain a constant vehicle speed. The output variable of the system is
vehicle speed. The input variable is the engine's torque output, which is regulated by
the throttle [9].
Engine and
other automobile systems are
increasingly
controlled
electronically. This has led to improved fuel economy, reduced pollution, improved
driving safety and