Intelligent Observer and Control Design for Nonlinear Systems

by Dierk Schröder (Editor), D. Schröder (Contribution by), U. Lenz (Contribution by), M. Beuschel (Contribution by), F.D. Hangl (Contribution by)

Overview

Control theory of nonlinear systems, in which either the linear part is known but the relevant nonlinearities in place, kind or parameters are unknown, or both the linear and the nonlinear parts are partially or even most unknown, is a new, demanding and highly interesting field. This book treats the problem by focussing on the role of learning. Intelligent learning techniques are able to determine the unknown components of nonlinear systems. These processes are always stable and convergent. The methods presented can be used both on-line and off-line. They have applications in mechatronics, hydraulics and combustion engines.

Product Details

ISBN-13:	9783642083464
Publisher:	Springer Berlin Heidelberg
Publication date:	11/10/2010
Edition description:	Softcover reprint of hardcover 1st ed. 2000
Pages:	339
Product dimensions:	6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

1 Introduction — Control Aspects.- 2 Motion Control.- 3 Learning in Control Engineering.- 4 Nonlinear Function Approximators.- 5 Systematic Intelligent Observer Design.- 6 Identification of Separable Nonlinearities.- 7 Identification and Compensation of Friction.- 8 Detection and Identification of Backlash.- 9 Identification of Isolated Nonlinearities in Rolling Mills.- 10 Input-Output Linearization: an Introduction.- 11 Stable Model Reference Neurocontrol.- 12 Dynamic Neural Network Compositions.- 13 Further Strategies for Nonlinear Control with Neural Networks.- List of Figures.