vii
TABLE OF CONTENTS
CHAPTER
1
TITLE
PAGE
DECLARATION
ii
DEDICATION
iii
ACKNOLEDGEMENTS
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
x
LIST OF FIGURES
xi
LIST OF SYMBOLS
xii
LIST OF ABBREVIATIONS
xiii
LIST OF APPENDICES
xiv
INTRODUCTION
1
1.1
Over view on PSO
1
1.2
Background of the Study
3
1.3
Statement of the problem
4
1.4
Objectives of the research
5
1.5
Scope of the project
6
1.6
Project time line
7
viii
2
LITERATURE REVIEW
8
2.1
Introduction
8
2.2
Description of Multi Robot Systems ( MRS )
9
2.2.1 Introduction
9
2.2.2 Taxonomy in MRS
10
2.2.3 Duties and domains for MRS
14
2.2.4 Unsupervised learning
15
Overview on Particle Swarm Optimization ( PSO )
16
2.3.1 Introduction
16
2.3.2 Classic PSO
17
2.3.3 The algorithm
20
2.3.4 PSO parameter control
21
2.3.5 Advantages of PSO
23
2.4
Previous investigations and works
24
2.5
Chapter Summary
27
2.3
3
4
METHODOLOGY
28
3.1
Introduction
28
3.2
Model Description
29
3.3
Modified Particle Swarm Algorithm (MPSA)
32
3.4
Fitness Function
33
3.5
Obstacle Avoidance
34
3.6
Collision Avoidance
36
3.7
Algorithm
37
3.8
Chapter Summary
38
SIMULATION RESULTS AND DISCUSSION
39
4.1
39
4.2
Introduction
Simulation Set-Up
41
4.2.1
Case study 1
43
4.2.2
Case study 2
45
ix
4.2.3
5
Case study 3
47
4.3
Comparison of simulations with other approaches
49
4.4
Discussion
50
CONCLUSION AND DISCUSSION
51
5.1
Conclusion
51
5.2
Recommendation of Future Works
52
REFERENCES
54
Appendices
58
x
LIST OF TABLES
TABLE NO.
1.1
TITLE
project time table
PAGE
7
xi
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
1.1
Swarm of birds
2
1.2
schools of fish
4
2.1
MRS Taxonomy
16
3.1
The neighborhood description for an agent
31
3.2
Change of the leader in the swarm
35
3.3
Virtual zone
36
4.1
Case study 1
43
4.2
Case study 2
45
4.3
Case study 3
47
xii
LIST OF SYMBOLS
Xi,j
-
Position of the particle i in dimension j
Vi,j
-
Velocity of the particle i in dimension j
-
Inertia weight
-
Random function
lbest
-
Local best
gbest
-
Global best
-
Inertia weight
-
Learning factor
-
Positive Constant coefficient
-
Fitness function
-
Maximum velocity bound
-
Minimum velocity bound
-
Best position of a particle
-
Best position of all particles
-
Penalty value
-
Fitness function
-
Set of obstacles
-
Position of the obstacle j
-
Penalty parameter
-
Penalty parameter
-
Threshold radios of the virtual zone for an agent
-
Distance between two agents
-
Number of Obstacles
-
Number of agents
-
Symbol of norm
xiii
LIST OF ABBREVIATIONS
PSO
-
Particle Swarm Optimization
3_D
-
Three Dimensional
MARS
-
Multiple Agent Robotic System
ODE
-
Ordinary Differential Equation
LTI
-
Linear Time Invariant
MRS
-
Multi Robot System
MPSA
-
Modified Particle Swarm Algorithm
GA
-
Genetic Algorithm
SISO
-
Single Input _ Single Output
MIMO
-
Multi Input _ Multi Output
ANN
-
Artificial Neural Networks
PID
-
Proportional Integral Derivative
xiv
LIST OF APPENDICES
APPENDIX.
A
TITLE
MATLAB Source Code ( m.file )
PAGE
64