Overview
- Easy and intuitive understanding
- Explanations and terminology from an engineering point-of-view
- Only basic mathematics required
- Self-contained, no other literature needed
- Includes supplementary material: sn.pub/extras
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About this book
The goal of this book is to provide engineers and scientIsts in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. The reader will be able to apply the discussed models and methods to real problems with the necessary confidence and the awareness of potential difficulties that may arise in practice. This book is self-contained in the sense that it requires merely basic knowledge of matrix algebra, signals and systems, and statistics. Therefore, it also serves as an introduction to linear system identification and gives a practical overview on the major optimization methods used in engineering. The emphasis of this book is on an intuitive understanding of the subject and the practical application of the discussed techniques. It is not written in a theorem/proof style; rather the mathematics is kept to a minimum and the pursued ideas are illustrated by numerous figures, examples, and real-world applications. Fifteen years ago, nonlinear system identification was a field of several ad-hoc approaches, each applicable only to a very restricted class of systems. With the advent of neural networks, fuzzy models, and modern structure opti mization techniques a much wider class of systems can be handled. Although one major characteristic of nonlinear systems is that almost every nonlinear system is unique, tools have been developed that allow the use of the same ap proach for a broad variety of systems.
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Table of contents (22 chapters)
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Front Matter
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Introduction
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Optimization Techniques
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Front Matter
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Back Matter
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Back Matter
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Dynamic Models
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Front Matter
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Authors and Affiliations
Bibliographic Information
Book Title: Nonlinear System Identification
Book Subtitle: From Classical Approaches to Neural Networks and Fuzzy Models
Authors: Oliver Nelles
DOI: https://doi.org/10.1007/978-3-662-04323-3
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 2001
Hardcover ISBN: 978-3-540-67369-9Published: 06 November 2000
Softcover ISBN: 978-3-642-08674-8Published: 15 December 2010
eBook ISBN: 978-3-662-04323-3Published: 09 March 2013
Edition Number: 1
Number of Pages: XVII, 786
Topics: Control and Systems Theory, Control, Robotics, Mechatronics, Complexity, Calculus of Variations and Optimal Control; Optimization, Simulation and Modeling