Poznyak A.S., Sanchez E.N., Yu W. Differential Neural Networks for Robust Nonlinear Control. Identification, State Estimation and Trajectory Tracking

Издательство World Scientific, 2001, -454 pp.This book deals with Continuous Time Dynamic Neural Networks Theory applied to solution of basic problems arising 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 a priory unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The high effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical and etc.).
The main aim of this book is to develop a systematic analysis for the applications of dynamic neural networks for identification, estimation and control of a wide class of nonlinear systems. The principal tool used to establish this analysis is a Lyapunov like technique. The applicability of the results, for both identification and robust control, is illustrated by different technical examples such as: chaotic systems, robotics and chemical processes.
The book could be used for self learning as well as a textbook. The level of competence expected for the reader is that covered in the courses of differential equations, the nonlinear systems analysis, in particular, the Lyapunov methodology, and some elements of the optimization theory.I Theoretical Study
Neural Networks Structures
Nonlinear System Identification: Differential Learning
Sliding Mode Identification: Algebraic Learning
Neural State Estimation
Passivation via Neuro Control
Neuro Trajectory Tracking
II Neurocontrol Applications
Neural Control for Chaos
Neuro Control for Robot Manipulators
Identification of Chemical Processes
Neuro-Control for Distillation Column
General Conclusions and future work
A: Some Useful Mathematical Facts
B: Elements of Qualitative Theory of ODE
C: Locally Optimal Control and Optimization