A nonlinear system identification method based on local linear PLS method

Takashi Shikimori, Hideo Muroi, Shuichi Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nonlinear system identification is one of the most important topics in system identification theory. In this paper, a new nonlinear system identification method using Partial Least-Squares (PLS) method is proposed, which is called a local linear PLS method because it is based on local models. The proposed method consists of two steps. First step is to identify local linear models by using the conventional Recursive Least-Squares (RLS) method. Second step is to identify a virtual system which describes a nonlinearity of the identified object, by PLS method. The effectiveness of the proposed method is shown through numerical simulations.

Original languageEnglish
Title of host publicationProceedings of the 13th IASTED International Conference on Intelligent Systems and Control, ISC 2011
Pages41-47
Number of pages7
DOIs
Publication statusPublished - 2011 Nov 9
Event13th IASTED International Conference on Intelligent Systems and Control, ISC 2011 - Cambridge, United Kingdom
Duration: 2011 Jul 112011 Jul 13

Publication series

NameProceedings of the IASTED International Conference on Intelligent Systems and Control
ISSN (Print)1025-8973

Other

Other13th IASTED International Conference on Intelligent Systems and Control, ISC 2011
CountryUnited Kingdom
CityCambridge
Period11/7/1111/7/13

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Keywords

  • Identification
  • Local linear model
  • Nonlinear systems
  • Partial least-squares (PLS) method
  • Recursive least-squares (RLS) method

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Modelling and Simulation
  • Artificial Intelligence

Cite this

Shikimori, T., Muroi, H., & Adachi, S. (2011). A nonlinear system identification method based on local linear PLS method. In Proceedings of the 13th IASTED International Conference on Intelligent Systems and Control, ISC 2011 (pp. 41-47). (Proceedings of the IASTED International Conference on Intelligent Systems and Control). https://doi.org/10.2316/P.2011.744-026