Differential neural networks for robust nonlinear control : identification, state estimation and trajectory tracking /
This volume deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be...
Clasificación: | Libro Electrónico |
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Autor principal: | |
Otros Autores: | , |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
River Edge, NJ :
World Scientific,
©2001.
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Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 0.1 Abstract ; 0.2 Preface ; 0.3 Acknowledgments ; 0.4 Introduction ; 0.4.1 Guide for the Readers ; 0.5 Notations ; I Theoretical Study ; 1 Neural Networks Structures ; 1.1 Introduction ; 1.2 Biological Neural Networks ; 1.3 Neuron Model.
- 1.4 Neural Networks Structures 1.4.1 Single-Layer Feedforward Networks ; 1.4.2 Multilayer Feedforward Neural Networks ; 1.4.3 Radial Basis Function Neural Networks ; 1.4.4 Recurrent Neural Networks ; 1.4.5 Differential Neural Networks ; 1.5 Neural Networks in Control.
- 1.5.1 Identification 1.5.2 Control ; 1.6 Conclusions ; 1.7 References ; 2 Nonlinear System Identification: Differential Learning ; 2.1 Introduction ; 2.2 Identification Error Stability Analysis for Simplest Differential Neural Networks without Hidden Layers.
- 2.2.1 Nonlinear System and Differential Neural Network Model 2.2.2 Exact Neural Network Matching with Known Linear Part ; 2.2.3 Non-exact Neural Networks Modelling: Bounded Unmodelled Dynamics Case.
- 2.2.4 Estimation of Maximum Value of Identification Error for Nonlinear Systems with Bounded Unmodelled Dynamics 2.3 Multilayer Differential Neural Networks for Nonlinear System On-line Identification ; 2.3.1 Multilayer Structure of Differential Neural Networks.