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 |
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ページ | 1211-1216 |
ページ数 | 6 |
出版ステータス | Published - 1995 12月 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月 26 → 1995 7月 28 |
Other
Other | Proceedings of the 34th SICE Annual Conference |
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City | Hokkaido, Jpn |
Period | 95/7/26 → 95/7/28 |
ASJC Scopus subject areas
- 制御およびシステム工学
- コンピュータ サイエンスの応用
- 電子工学および電気工学