| 作 者： | 刘金琨 |
| 出版社： | 清华大学出版社 |
| 丛编项： | |
| 版权说明： | 本书为公共版权或经版权方授权，请支持正版图书 |
| 标 签： | 计算机/网络 人工智能 |
| ISBN | 出版时间 | 包装 | 开本 | 页数 | 字数 |
|---|---|---|---|---|---|
| 未知 | 暂无 | 暂无 | 未知 | 0 | 暂无 |
Contents Chapter 1 Introduction 1.1 Neural Network Control 1.1.1 Why Neural Network Control? 1.1.2 Review of Neural Network Control 1.1.3 Review of RBF Adaptive Control 1.2 Review of RBF Neural Network 1.3 RBF Adaptive Control for Robot Manipulators 1....
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Appendix Chapter 2 RBF Neural Network Design and Simulation 2.1 RBF Neural Network Design and Simulation 2.1.1 RBF Algorithm 2.1.2 RBF Design Example with Matlab Simulation 2.2 RBF Neural Network Approximation Based on Gradient Descent Method
2.2.1 RBF Neural Network Approximation 2.2.2 Simulation Example 2.3 Effect of Gaussian Function Parameters on RBF Approximation 2.4 Effect of Hidden Nets Number on RBF Approximation 2.5 RBF Neural Network Training for System Modeling 2.5.1 RBF Neural N...
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Appendix Chapter 3 RBF Neural Network Control Based on Gradient Descent Algorithm
3.1 Supervisory Control Based on RBF Neural Network 3.1.1 RBF Supervisory Control 3.1.2 Simulation Example 3.2 RBFNN Based Model Reference Adaptive Control 3.2.1 Controller Design 3.2.2 Simulation Example 3.3 RBF Self-Adjust Control 3.3.1 System Descri...
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Appendix Chapter 4 Adaptive RBF Neural Network Control 4.1 Adaptive Control Based on Neural Approximation 4.1.1 Problem Description 4.1.2 Adaptive RBF Controller Design 4.1.3 Simulation Examples 4.2 Adaptive Control Based on Neural Approximation with U...
4.2.1 Problem Description 4.2.2 Adaptive Controller Design 4.2.3 Simulation Examples 4.3 A Direct Method for Robust Adaptive Control by RBF 4.3.1 System Description 4.3.2 Desired Feedback Control and Function Approximation 4.3.3 Controller Design and P...
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Appendix Chapter 5 Neural Network Sliding Mode Control 5.1 Typical Sliding Mode Controller Design 5.2 Sliding Mode Control Based on RBF for Second-Order SISO Nonlinear System
5.2.1 Problem Description 5.2.2 Sliding Mode Control Based on RBF for Unknown f().
5.2.3 Simulation Example 5.3 Sliding Mode Control Based on RBF for Unknown f(). and g().
5.3.1 Introduction 5.3.2 Simulation Example References
Appendix Chapter 6 Adaptive RBF Control Based on Global Approximation 6.1 Adaptive Control with RBF Neural Network Compensation for Robotic Manipulators
6.1.1 Problem Description 6.1.2 RBF Approximation 6.1.3 RBF Controller and Adaptive Law Design and Analysis 6.1.4 Simulation Examples 6.2 RBF Neural Robot Controller Design with Sliding Mode Robust Term
6.2.1 Problem Description 6.2.2 RBF Approximation 6.2.3 Control Law Design and Stability Analysis 6.2.4 Simulation Examples 6.3 Robust Control Based on RBF Neural Network with HJI 6.3.1 Foundation 6.3.2 Controller Design and Analysis 6.3.3 Simulation E...
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Appendix Chapter 7 Adaptive Robust RBF Control Based on Local Approximation
7.1 Robust Control Based on Nominal Model for Robotic Manipulators
7.1.1 Problem Description 7.1.2 Controller Design 7.1.3 Stability Analysis 7.1.4 Simulation Example 7.2 Adaptive RBF Control Based on Local Model Approximation for Robotic Manipulators
7.2.1 Problem Description 7.2.2 Controller Design 7.2.3 Stability Analysis 7.2.4 Simulation Examples 7.3 Adaptive Neural Network Control of Robot Manipulators in Task Space
7.3.1 Coordination Transformation from Task Space to Joint Space
7.3.2 Neural Network Modeling of Robot Manipulators 7.3.3 Controller Design 7.3.4 Simulation Examples
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Appendix Chapter 8 Backstepping Control with RBF 8.1 Introduction 8.2 Backstepping Control for Inverted Pendulum 8.2.1 System Description 8.2.2 Controller Design 8.2.3 Simulation Example 8.3 Backstepping Control Based on RBF for Inverted Pendulum 8.3.1...
8.5.1 Backstepping Controller Design with Function Estimation
8.5.2 Backstepping Controller Design with RBF Approximation
8.5.3 Simulation Examples
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Appendix Chapter 9 Digital RBF Neural Network Control 9.1 Adaptive Runge-Kutta-Merson Method 9.1.1 Introduction 9.1.2 Simulation Example 9.2 Digital Adaptive Control for SISO System 9.2.1 Introduction 9.2.2 Simulation Example 9.3 Digital Adaptive RBF C...
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Appendix Chapter 10 Discrete Neural Network Control 10.1 Introduction 10.2 Direct RBF Control for a Class of Discrete-time Nonlinear System
10.2.1 System Description 10.2.2 Controller Design and Stability Analysis 10.2.3 Simulation Examples 10.3 Adaptive RBF Control for a Class of Discrete-Time Nonlinear System
10.3.1 System Description 10.3.2 Traditional Controller Design 10.3.3 Adaptive Neural Network Controller Design 10.3.4 Stability Analysis 10.3.5 Simulation Examples
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Appendix Chapter 11 Adaptive RBF Observer Design and Sliding Mode Control
11.1 Adaptive RBF observer design 11.1.1 System Description 11.1.2 Adaptive RBF Observer Design and Analysis 11.1.3 Simulation Examples 11.2 Sliding Mode Control Based on RBF Adaptive Observer 11.2.1 Sliding Mode Controller Design 11.2.2 Simulation Example
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Appendix Index
