Fuzzy Sliding Mode Control and Observation of Complex Dynamic Systems and Applications
￥46.00定价
作者： 乔枫 朱全民 张百海 著
出版时间：2013-11-01
出版社：北京理工大学出版社
以下为《Fuzzy Sliding Mode Control and Observation of Complex Dynamic Systems and Applications》的配套数字资源，这些资源在您购买图书后将免费附送给您：
- 北京理工大学出版社
- 9787564085339
- 1
- 108814
- 2013-11-01
- TP273
作者简介
内容简介
在复杂的现实世界中，组成工业设备的部件呈现特性的非线性性、结构的不确定性、参数的摄动，并受到外界扰动的影响，很难(甚至不可能)用数学方法对设备的行为进行精确的描述。在工程实际应用中，控制系统的稳定性和鲁棒性是至关重要的问题。本书针对复杂动态系统存在诸多问题，设计了基于滑模技术和模糊逻辑的控制系统设计方案，研究了系统的稳定性控制、跟踪控制、系统状态观测和参数估计等问题。
本书共分9章，其中：第1-5章主要为系统控制与观测的滑模理论研究；第6-9章为滑模技术在复杂动态系统中的应用。
本书共分9章，其中：第1-5章主要为系统控制与观测的滑模理论研究；第6-9章为滑模技术在复杂动态系统中的应用。
目录
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
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
