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Stable adaptive neural network control

Author: S S Ge
Publisher: Boston : Kluwer Academic, ©2002.
Series: Kluwer international series on Asian studies in computer and information science, 13.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals  Read more...

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: S S Ge
ISBN: 0792375971 9780792375975
OCLC Number: 48038244
Description: xvi, 282 pages : illustrations ; 24 cm.
Contents: 1 Introduction --
1.1 Introduction --
1.2 Adaptive Control --
1.3 Neural Network Control --
1.4 Instability Mechanisms in Adaptive Neural Control Systems --
1.5 Outline of the Book --
1.6 Conclusion --
2 Mathematical Preliminaries --
2.1 Introduction --
2.2 Mathematical Preliminaries --
2.2.1 Norms for Vectors and Signals --
2.2.2 Properties of Matrix --
2.3 Concepts of Stability --
2.4 Lyapunov Stability Theorem --
2.5 Useful Theorems and Formula --
2.5.1 Sliding Surface --
2.5.2 Mean Value Theorem --
2.5.3 Integral Formula --
2.5.4 Implicit Function Theorem --
2.5.5 Input-Output Stability --
2.6 Conclusion --
3 Neural Networks and Function Approximation --
3.1 Introduction. --
3.2 Function Approximation --
3.3 Linearly Parametrized Neural Networks --
3.4 Non-linearly Parametrized Networks --
3.5 Neural Networks for Control Applications --
3.6 Conclusion --
4 SISO Nonlinear Systems --
4.1 Introduction --
4.2 NN Control with Regional Stability --
4.2.1 Desired Feedback Control --
4.2.2 HONN Controller Design Based on (4.7) --
4.2.3 MNN Control Based on (4.10) --
4.3 VSC --
Semi-Global Stability --
4.3.1 VSC-based Adaptive NN Control Design --
4.3.2 Elimination for Controller Chattering --
4.3.3 Simulation Study --
4.4 Conclusion: --
5 ILF for Adaptive Control --
5.1 Introduction --
5.2 Matching SISO Nonlinear Systems --
5.2.1 Integral Lyapunov Function --
5.2.2 Choice of Weighting Function a(x) --
5.2.3 Adaptive NN Control Based on DFCs --
5.3 Backstepping Adaptive NN Design --
5.3.1 Adaptive Design for a First-order System --
5.3.2 Design for nth-order Systems --
5.3.3 Controller Design with Reduced Knowledge --
5.3.4 Simulation Studies --
5.4 NN Control for MIMO Nonlinear Systems --
5.4.1 System Description --
5.4.2 Lyapunov Function Design and Control Structure. --
5.4.3 Adaptive MIMO Control Using MNNs --
5.5 Conclusion --
6 Non-affine Nonlinear Systems --
6.1 Introduction --
6.2 System Description and Properties --
6.2.1 Implicit Desired Feedback Control --
6.2.2 High-gain Observer --
6.3 Controller Design Based on LPNN --
6.3.1 State Feedback Control --
6.3.2 Output Feedback Control --
6.3.3 Simulation Study --
6.4 Controller Design Based on MNN --
6.4.1 State Feedback Control --
6.4.2 Output Feedback Control --
6.4.3 Application to CSTR --
6.5 Conclusion --
7 Triangular Nonlinear Systems --
7.1 Introduction --
7.2 Special Systems in Strict-Feedback Form --
7.2.1 Direct Adaptive NN Control --
7.2.2 Simulation studies --
7.3 Partially Known Nonlinear Systems --
7.3.1 Adaptive Neural Control Design --
7.3.2 Numerical Simulation --
7.4 Pure-feedback Nonlinear Systems --
7.4.1 Direct Adaptive NN Control for 1E --
7.4.2 Direct Adaptive NN Control for E --
7.4.3 Simulation studies --
7.5 MIMO Nonlinear Systems --
7.6 Conclusion --
8 Conclusion --
8.1 Conclusion --
8.2 Design Flexibility --
8.3 Further Research
Series Title: Kluwer international series on Asian studies in computer and information science, 13.
Responsibility: by S.S. Ge [and others].
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