Generalized predictive control of fuzzy model based on genetic algorithm

被引：0

作者：

Li Shu-chen ^{[1
]}

Zhai Chun-yan ^{[1
]}

Xiao Jun ^{[1
]}

机构：

[1] Liaoning Univ Petr & Chem Technol, Sch Informat & Engn, Fushun 113001, Peoples R China

来源：

Proceedings of 2004 Chinese Control and Decision Conference | 2004年

关键词：

genetic algorithm; fuzzy model; generalized predictive control; nonlinear system;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new fuzzy predictive control is introduced by using genetic algorithm to solve its membership functions without self-adaptability and complexity of fuzzy rules defined subjectively in T-S fuzzy model of model predictive control. A generalized T-S fuzzy model is constructed for nonlinear system, and a suboptimal fuzzy,system model is attained by GA. Local dynamic linearization is applied to the system at each sampling point. Then control action is derived using generalized predictive control (GPC) based on the linearized model. Its effectiveness for nonlinear systems is verified via simulation result.

引用

页码：172 / 174

页数：3

共 6 条

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