Fuzzy neural network-based adaptive single neuron controller

被引：0

作者：

Jia, Li ^{[1
]}

Tao, Pengye ^{[1
]}

Chiu, MinSen ^{[2
]}

机构：

[1] Shanghai Univ, Coll Machatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

[2] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 119260, Singapore

来源：

BIO-INSPIRED COMPUTATIONAL INTELLIGENCE AND APPLICATIONS | 2007年 / 4688卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To circumvent the drawbacks in nonlinear controller designing of chemical processes, an adaptive single neuron control scheme is proposed in this paper. A class of nonlinear processes is approximated by a fuzzy neural network-based model. The key of this work is, an adaptive single neuron controller, which mimics PID controller, is considered in the proposed control scheme. Applying this result and Lyapunov stability theory, a novel-updating algorithm to adjust the parameters of the single neuron controller is presented. Simulation results illustrate the effectiveness of the proposed adaptive single neuron control scheme.

引用

页码：412 / +

页数：3

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