Identification of nonlinear systems based on adaptive fuzzy systems embedding Quasi-ARMAX model

Jinglu Hu, Kousuke Kumamaru

研究成果: Paper査読

抄録

This paper addresses the issues related to identification of nonlinear systems based on Adaptive Fuzzy Systems (AFSs) Embedding Quasi-ARMAX Model. A general nonlinear system can be represented as a Quasi-ARMAX form, in which the parameters āi and b̄i contain two parts: linear part and nonlinear part. By introducing and Adaptive Fuzzy System (AFS) to the nonlinear part of each parameter, we propose an AFSs Embedding Quasi-ARMAX Model for identification of nonlinear systems. Since the Quasi-ARMAX model consists of a combination of AFSs and ARMAX model, a priori information about system structure besides input-output data can be incorporated into the identification. Simulation results show that the proposed Quasi-ARMAX model has better performance than Neural Networks (NN) model.

本文言語English
ページ1211-1216
ページ数6
出版ステータスPublished - 1995 12 1
外部発表はい
イベントProceedings of the 34th SICE Annual Conference - Hokkaido, Jpn
継続期間: 1995 7 261995 7 28

Other

OtherProceedings of the 34th SICE Annual Conference
CityHokkaido, Jpn
Period95/7/2695/7/28

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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