A search algorithm for the identification of multiple inputs nonlinear systems using orthogonal least squares estimator

K. M. Tsang, Wai Lok Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)357-365
Number of pages9
JournalElectrical Engineering
Volume88
Issue number5
DOIs
Publication statusPublished - 1 Jun 2006

Keywords

  • Nonlinear systems
  • PFC boost converter
  • System identification

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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