Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32246
Title: A search algorithm for the identification of multiple inputs nonlinear systems using orthogonal least squares estimator
Authors: Tsang, KM 
Chan, WL 
Keywords: Nonlinear systems
PFC boost converter
System identification
Issue Date: 2006
Publisher: Springer
Source: Electrical engineering, 2006, v. 88, no. 5, p. 357-365 How to cite?
Journal: Electrical Engineering 
Abstract: A search algorithm for the identification of multiple inputs nonlinear systems using the orthogonal least squares estimator is derived. Because of the high dimensionality of general nonlinear systems the forward regression algorithm is used to detect the plausible size of the final fitted model and a variation of the forward regression algorithm is proposed. Instead of choosing the best candidate term at each iteration, top few candidate terms which have the largest error reduction ratios are investigated at each iteration. A search algorithm coupled with the model predicted output is derived which will sort through all plausible candidate terms to produce an optimal solution for the problem. Simulated and experimental examples are included to demonstrate the effectiveness of the proposed algorithm.
URI: http://hdl.handle.net/10397/32246
ISSN: 0948-7921
DOI: 10.1007/s00202-005-0293-3
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