A hybrid learning method for B-spline fuzzy neural control system

被引：0
|
作者：
Liu, Quart [1 ]
Lv, Lin
Luan, Baohong
机构：
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Peoples R China
[2] Xiangfan Branch MEA, Xiangfan 441118, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13E卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A novel controller based on the fuzzy B-spline NN is being introduced, which combines the advantages of qualitative defining capability of fuzzy logic and quantitative learning ability of NN, and uses B-spline as membership of fuzzy functions. Simultaneously, a hybrid learning method of the controller is proposed as well, in which the immune genetic algorithm(IGA) is used offline first for optimizing, followed by online adjustment with the Levenberg-Marquardt(LM) algorithm. Simulation results of a boiler's fresh steam temperature control shows the method to be feasible and effective.
引用
收藏
页码：3090 / 3093
页数：4
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