Self Tuning Fuzzy Controller of Nonlinear Systems

被引:0
|
作者
Sahraoui, Mustapha [1 ]
Salem, Mohammed [1 ]
Khelfi, Med Faycal [2 ]
机构
[1] Univ Mascara, Fac Sci & Technol, Mascara, Algeria
[2] Univ Oran Senia, Fac Sci, RIIR Lab, oran, Algeria
关键词
Artificial Intelligence; STFIS (Self Tuning Fuzzy Inference System); neuro-fuzzy networks; neural networks; nonlinear system; control;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The present paper is dedicated for the presentation and implementation of an optimized technique allowing an on-line adjustment of the fuzzy controller parameters. Indeed, we have obtained an on-line optimized zero order Takagi-Sugeno type FIS. This method is simple and safe since, it leads to very quick and efficient optimization technique. A comparison between the STFIS (Self Tuning Fuzzy Inference System) and PID controller's gives the improvement of the ability in sense of adaptation among the presence of noise of neuro-fuzzy controller.
引用
收藏
页码:912 / 915
页数:4
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