Multivariable adaptive fuzzy predictive control based on T-S model

Fu Cai Liu; Li Na Ren; Ping Li Lu

doi:10.3969/j.issn.1001-506X.2010.12.34

Multivariable adaptive fuzzy predictive control based on T-S model

Fu Cai Liu^*, Li Na Ren, Ping Li Lu

^*此作品的通讯作者

自动化学院

Yanshan University

科研成果: 期刊稿件 › 文章 › 同行评审

3 引用（Scopus）

摘要

A very good control effect algorithm of fuzzy predictive control based on nonlinear multivariable system is presented. Firstly, the nonlinear system of T-S model is identified by fast clustering and recursive least square method, and the linear model is gotten. Then the fuzzy generalized predictive controller based on linear system is designed to control the nonlinear object adaptively. The simulations for the variable nonlinear object with delay time and strong coupling show that this algorithm has good control effects.

源语言	英语
页（从-至）	2660-2663
页数	4
期刊	Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
卷	32
期	12
DOI	https://doi.org/10.3969/j.issn.1001-506X.2010.12.34
出版状态	已出版 - 12月 2010

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title = "Multivariable adaptive fuzzy predictive control based on T-S model",

abstract = "A very good control effect algorithm of fuzzy predictive control based on nonlinear multivariable system is presented. Firstly, the nonlinear system of T-S model is identified by fast clustering and recursive least square method, and the linear model is gotten. Then the fuzzy generalized predictive controller based on linear system is designed to control the nonlinear object adaptively. The simulations for the variable nonlinear object with delay time and strong coupling show that this algorithm has good control effects.",

keywords = "Adaptive control, Fast fuzzy clustering, Generalized predictive control, T-S model",

author = "Liu, {Fu Cai} and Ren, {Li Na} and Lu, {Ping Li}",

year = "2010",

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doi = "10.3969/j.issn.1001-506X.2010.12.34",

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AU - Ren, Li Na

AU - Lu, Ping Li

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N2 - A very good control effect algorithm of fuzzy predictive control based on nonlinear multivariable system is presented. Firstly, the nonlinear system of T-S model is identified by fast clustering and recursive least square method, and the linear model is gotten. Then the fuzzy generalized predictive controller based on linear system is designed to control the nonlinear object adaptively. The simulations for the variable nonlinear object with delay time and strong coupling show that this algorithm has good control effects.

AB - A very good control effect algorithm of fuzzy predictive control based on nonlinear multivariable system is presented. Firstly, the nonlinear system of T-S model is identified by fast clustering and recursive least square method, and the linear model is gotten. Then the fuzzy generalized predictive controller based on linear system is designed to control the nonlinear object adaptively. The simulations for the variable nonlinear object with delay time and strong coupling show that this algorithm has good control effects.

KW - Adaptive control

KW - Fast fuzzy clustering

KW - Generalized predictive control

KW - T-S model

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JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics

IS - 12

ER -

Multivariable adaptive fuzzy predictive control based on T-S model

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