Adaptive predictor for control of nonlinear systems based on neurofuzzy models

J. Hu, K. Hirasawa, K. Kumamaru

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

1 Citation (Scopus)

Abstract

This paper proposes a general nonlinear adaptive predictor using a class of neurofuzzy models. The obtained predictor may be seen as a linear predictor network consisting of a global linear predictor and several local linear predictors with interpolation. It has distinctive features as well as good prediction ability: its parameters have explicit meanings useful for initial values setting: it may be transformed into a form linear for the variables synthesized in control systems, making deriving a control law straightforward.

Original languageEnglish
Title of host publicationEuropean Control Conference, ECC 1999 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4337-4342
Number of pages6
ISBN (Electronic)9783952417355
DOIs
Publication statusPublished - 2015 Mar 24
Event1999 European Control Conference, ECC 1999 - Karlsruhe, Germany
Duration: 1999 Aug 311999 Sep 3

Publication series

NameEuropean Control Conference, ECC 1999 - Conference Proceedings

Other

Other1999 European Control Conference, ECC 1999
CountryGermany
CityKarlsruhe
Period99/8/3199/9/3

Keywords

  • AR-MAX modeling
  • Nonlinear system
  • adaptive prediction
  • neurofuzzy model
  • nonlinear control

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'Adaptive predictor for control of nonlinear systems based on neurofuzzy models'. Together they form a unique fingerprint.

  • Cite this

    Hu, J., Hirasawa, K., & Kumamaru, K. (2015). Adaptive predictor for control of nonlinear systems based on neurofuzzy models. In European Control Conference, ECC 1999 - Conference Proceedings (pp. 4337-4342). [7100016] (European Control Conference, ECC 1999 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ecc.1999.7100016