Preface

Table of Contents

Abbreviations

Symbols

1 Literature survey and background

　1.1 Introduction

　1.2 Variable structure systems

　1.3 Discrete time variable structure control systems

　1.4 Fusion of artificial intelligence algorithms with SMC

　　1.4.1 Artificialintelligence

　　1.4.2 Fuzzy sliding mode control

　　1.4.3 Adaptive fuzzy sliding mode contro

　　1.4.4 Neural network based sliding mode control

　　1.4.5 Neural fuzzy based sliding mode control

　1.5 Sliding mode observation

　1.6 Applications and practice of sliding mode control

　1.7 Summary

2 Preliminarymethodologies

　2.1 Introduction

　2.2 Nonlinear systems and their control

　　2.2.1 Nonlinear systems

　　2.2.2 Controlofnonlinear systems

　2.3 Variable structure control

　　2.3.1 Variable structure systems

　　2.3.2 Sliding mode in variable structure systems

　　2.3.3 Sliding mode control design by the reaching law approach

　2.4 Discrete time sliding mode control

　　2.4.1 Discrete time sliding mode control

　　2.4.2 DSMC control design by the reaching law approach

　2.5 Fuzzy logic control

　　2.5.1 Mamdani fuzzylogic systems

　　2.5.2 Takagi—sugeno fuzzylogic systems

　2.6 Fuzzy adaptive control

　2.7 Summary

3 Adaptive fuzzy sliding mode control

　3.1 Introduction

　3.2 Fuzzy universal approximation

　　3.2.1 Fuzzy basis functions

　　3.2.2 Fuzzy universal approximation

　3.3 AFSMC for SISO nonlinear systems

　　3.3.1 Problem statement

　　3.3.2 Conventional sliding mode control

　　3.3.3 Indirect adaptive control law based on fuzzy logic schemes

　　3.3.4 Lyapunov stability analysis

　　3.3.5 Simulation studies

　3.4 AFSMC for MIMO nonlinear systems

　　3.4.1 Problem statement

　　3.4.2 Conventional sliding mode control

　　3.4.3 Adaptive fuzzy controllaw design

　　3.4.4 Simulation studies

　3.5 Summary

4 Sliding mode observation

　4.1 Introduction

　4.2 State observation

　4.3 Sliding mode observation

　4.4 Nonlinear sliding mode observers for stochastic systems

　　4.4.1 Preliminaries and problem formulation

　　4.4.2 Adaptive sliding mode observer design

　　4.4.3 Convergence analysis of the observer

　　4.4.4 Simulation studies

　4.5 Summary

5 Adapave observer based nonlinear stochastic system control with sliding mode schemes

　5.1 Introduction

　5.2 Problem statement and preliminaries

　5.3 Adaptive observer design based on sliding mode schemes

　　5.3.1 Design of the observer

　　5.3.2 Convergence of the observer

　5.4 Adaptive observer based nonlinear stochastic system control

　　5.4.1 Sliding mode controller based on sliding mode observer

　　5.4.2 Stability analysis ofoverall closed—loop systems

　5.5 Simulation studies

　5.6 Summary

6 Hovering control of a helicopter simulator

　6.1 Overview ofhovering control

　6.2 Dynamic models of helicopter simulator

　　6.2.1 Aerodynamic analysis of rotor thrust

　　6.2.2 Mathematical models ofhelicopter simulator

　　6.2.3 Time discretization ofnonlinear systems

　6.3 Fuzzy sliding mode controller design

　　6.3.1 Perfect control law

　　6.3.2 Design of controller

　　6.3.3 Design procedures for controller

　6.4 Simulation studies

　　6.4.1 Parameters and initial conditions

　　6.4.2 Design of conventional fuzzy logic control

　　6.4.3 Simulation results

　6.5 Summary

7 Adaptive control for robotic manipulators

　7.1 Overview of the control ofrobotic manipulators

　7.2 Dynamic models ofrobot manipulators

　7.3 Rigid and flexiblejoint robotic manipulators

　7.4 Dynamics of a two—link rigid robot manipulator

　7.5 Controller design for an SCARA robot

　7.6 Simulation studies

　7.7 Summary

8 Controller design for vehicle suspension systems

　8.1 Overview ofvehicle suspension systems

　　8.1.1 Velucle suspension systems

　　8.1.2 Literature review

　8.2 Mathematical models and control problem

　　8.2.1 System dynamic model

　　8.2.2 Objective ofcontrol

　8.3 Proportionalintegralsliding mode control