Intelligent Observer and Control Design for Nonlinear Systems (1999, Hardcover)

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Last updated on 07 Jul, 2025 19:17:52 BSTView all revisionsView all revisions

Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Educational Level
College, Professional
Level
Intermediate, Advanced, Technical
ISBN
9783540636397
Category

About this product

Product Identifiers

Publisher
Springer Berlin / Heidelberg
ISBN-10
3540636390
ISBN-13
9783540636397
eBay Product ID (ePID)
1662095

Product Key Features

Number of Pages
Xiii, 339 Pages
Publication Name
Intelligent Observer and Control Design for Nonlinear Systems
Language
English
Subject
Automation, Mechanics / Dynamics, Mechanical, Electrical
Publication Year
1999
Type
Textbook
Subject Area
Technology & Engineering, Science
Author
U. Lenz
Format
Hardcover

Dimensions

Item Weight
52.9 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
99-049192
Dewey Edition
21
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
629.8
Table Of Content
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.
Synopsis
This application-oriented monograph focuses on a novel and complex type of control systems. Written on an engineering level, including fundamentals, advanced methods and applications, the book applies techniques originating from new methods such as artificial intelligence, fuzzy logic, neural networks etc., 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.
LC Classification Number
TJ212-225

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