Hammerstein model identification algorithm using Bezier-Bernstein approximation

Hong, X. ORCID: https://orcid.org/0000-0002-6832-2298 and Mitchell, R. J. (2007) Hammerstein model identification algorithm using Bezier-Bernstein approximation. IET Control Theory and Applications, 1 (4). pp. 1149-1159. ISSN 1751-8644 doi: 10.1049/iet-cta:20060018

Abstract/Summary

A new identification algorithm is introduced for the Hammerstein model consisting of a nonlinear static function followed by a linear dynamical model. The nonlinear static function is characterised by using the Bezier-Bernstein approximation. The identification method is based on a hybrid scheme including the applications of the inverse of de Casteljau's algorithm, the least squares algorithm and the Gauss-Newton algorithm subject to constraints. The related work and the extension of the proposed algorithm to multi-input multi-output systems are discussed. Numerical examples including systems with some hard nonlinearities are used to illustrate the efficacy of the proposed approach through comparisons with other approaches.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/15285
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Uncontrolled Keywords	ORTHOGONAL LEAST-SQUARES, SYSTEM-IDENTIFICATION, REGRESSION
Download/View statistics	View download statistics for this item