Wavelet Network Based Nonlinear System Identification
Liu, G.P., Billings, S.A. and Kadirkamanathan, V
(1996)
Wavelet Network Based Nonlinear System Identification.
Research Report.
ACSE Research Report 657
.
Department of Automatic Control and Systems Engineering
Abstract
Identification schemes using wavelet networks are presented for nonlinear dynamical systems. Based on fixed wavelet networks , parameter adaptation laws are developed using a Lyapunov synthesis approach. This guarantees the stability of the overall identification scheme and the convergence of both the parameters and the state errors, even in the presence of modelling errors. Using the decomposition and reconstruction techniques of multiresolution decompositions, variable wavelet networks are introduced to achieve a desired estimation accuracy and a suitable sized network and to adapt to variations of the characteristics and operating points in nonlinear systems. B-spline wavelets are used to form the wavelet networks and the identification scheme is illustrated using a simulated example.
Metadata
Item Type:
Monograph
Authors/Creators:
Liu, G.P.
Billings, S.A.
Kadirkamanathan, V
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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