NDLI: A T-S model identification method based on harmony search algorithm

Content Provider	IEEE Xplore Digital Library
Author	Huang Xianlin Song Qingnan Ban Xiaojun Gao Xiaozhi
Copyright Year	2010
Description	Author affiliation: Center for Control Theory and Guidance Technology, Harbin Institute of Technology, 150001, China (Huang Xianlin; Song Qingnan; Ban Xiaojun; Gao Xiaozhi)
Abstract	The conventional T-S fuzzy model identification methods, such as the fuzzy c-means (FCM) algorithm and least-squares method, usually fail to find the optimal solutions, because they determine the consequent parameters based on only one certain group of the premise parameters. That is to say, these techniques are usually trapped into the local optima in the multidimensional parameter space. In the present paper, a new hybrid identification algorithm(HIA) is introduced to overcome the above drawback. Our method can simultaneously optimize the premise and consequent parameters by merging the harmony search algorithm(HS), FCM algorithm and least-squares method together. This hybrid approach also has the remarkable feature of error feedback mechanism. Simulation results demonstrate that the proposed optimization algorithm can effectively escape from the local optima, and yield a superior performance over the regular parameter identification methods.
Starting Page	1224
Ending Page	1229
File Size	433021
Page Count	6
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Electrical engineering Barium Error Feedback Mechanism Simulation Merging T-S Model Identification Electronic mail Control theory Harmony Search (HS) Hybrid Identification Algorithm(HIA) Optimization Local Optima
Content Type	Text
Resource Type	Article

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