Wavelet-based system identification for nonlinear control

Compactly supported orthogonal wavelets have certain properties that are useful for system identification and learning control. Drawing on the rich theory of wavelets, we propose a system identification scheme based on orthogonal wavelets. Better accuracy of estimation can be obtained by adding more...

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Bibliographic Details
Published in:IEEE transactions on automatic control 1999-02, Vol.44 (2), p.412-417
Main Authors: Sureshbabu, N., Farrell, J.A.
Format: Article
Language:English
Subjects:
Adaptive control
Applied sciences
Automatic control
Computer science
control theory
systems
Control systems
Control theory. Systems
Electric vehicles
Exact sciences and technology
Filters
Function approximation
Learning
Modelling and identification
Nonlinear control systems
Nonlinear systems
Nonlinearity
Parameter estimation
System identification
Uncertainty
Wavelet
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Summary:Compactly supported orthogonal wavelets have certain properties that are useful for system identification and learning control. Drawing on the rich theory of wavelets, we propose a system identification scheme based on orthogonal wavelets. Better accuracy of estimation can be obtained by adding more terms to the wavelet based identifier, and these terms do not alter the coefficients of the existing terms. These terms can be selectively added depending upon the region of interest, for example we may require more terms in regions where the identified functions vary rapidly. We illustrate the concepts by applying the procedure to determine a speed-controller for an electric vehicle.
ISSN:0018-9286
1558-2523
DOI:10.1109/9.746278