Nonlinear System Identification : Input-Output Modeling Approach

Haber, Robert; Keviczky, Laszlo

ISBN 10: 0792358589 / ISBN 13: 9780792358589

Published by Springer, 1999

About this Item

Seller Inventory # 5153388-n

Bibliographic Details

• Title: Nonlinear System Identification : Input-Output Modeling Approach
• Publisher: Springer
• Publication Date: 1999
• Language: English
• ISBN 10: 0792358589
• ISBN 13: 9780792358589
• Binding: Hardcover
• Condition: New

About this title

Synopsis

The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.

Synopsis

This two-volume handbook presents a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes: modelling, parameter estimation, structure search, nonlinearity and model validity tests. The book includes not only nonparametric models but also parametric models which include a limited number of parameters. Time domain parameter estimation is dealt with in detail; frequency domain and power spectrum procedures are also included. This work is intended for postgraduate students, researchers and engineers whose work involves nonlinear systems. Many examples, case studies and experimental identifications of real processes have been included.