Operating Regime Determination in Fuzzy Local Modeling by Genetic Algorithm

Michiaki Ishida; Toshiharu Hatanaka; Katsuji Uosaki

doi:10.11499/sicep.2002.0.441.0

SICE Annual Conference 2002

DOI https://doi.org/10.11499/sicep.2002.0.441.0

Conference information

Host: The Society of Instrument and Control Engineers

Co-host: IEEE/Industiral Electronic Society, IEEE/Robotics and Automation Society, IEEE/Control System Society

Operating Regime Determination in Fuzzy Local Modeling by Genetic Algorithm

Michiaki Ishida, Toshiharu Hatanaka, Katsuji Uosaki

Author information

Keywords: Fuzzy modeling, local modeling, Takagi-Sugeno fuzzy model, nonlinear system identification, complex system, genetic algorithm

CONFERENCE PROCEEDINGS FREE ACCESS

Pages 441

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Abstract

Recently, fuzzy local modeling has attracted attention to identify the complex systems. In this approach, a global system model is represented by the combination of a number of simple local models and each local model is identified for corresponding local operating regimes defined by membership function. This paper addresses automatic determination algorithm for membership functions to give suitable local operating regimes in fuzzy local modeling based on genetic algorithm. Numerical simulation results show the applicability of the proposed algorithm.

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