Fuzzy Neural Network Control and Identification for Uncertain Nonlinear Systems

被引：0
|
作者：
Ji, Xiu-Huan [1 ]
机构：
[1] Linyi Normal Univ, Coll Informat, Linyi 276005, Peoples R China
来源：
2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5 | 2010年
关键词：
Neural network; Adaptive; Control; Identification; Nonlinear system; INFINITY TRACKING DESIGN; FAULT-TOLERANT CONTROL; ADAPTIVE-CONTROL; SISO SYSTEMS; APPROXIMATION;
D O I：
10.1109/CCDC.2010.5498390
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the problem of identification and control of uncertain nonlinear systems is investigated based on fuzzy neural network. The considered systems are unknown and with external disturbances, so fuzzy neural networks are employed to approximate the unknown system functions. By doing this, an identification model of the controlled system can be obtained. Based on this model, a controller with adaptive mechanism can be designed for the system. The controller can attenuate the external disturbance to a given level, and guarantee the stability of the closed-loop system. Satisfactory identification and control of the system can be realized at the same time. Simulation example is given to demonstrate the effectiveness of the proposed controller.
引用
收藏
页码：4237 / 4242
页数：6
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