PID neural network in multivariable time-varying systems

被引：0

作者：

Shu, HL ^{[1
]}

Shu, L

机构：

[1] Guangzhou Univ, Dept Informat & Control Engn, Guangzhou, Peoples R China

[2] Wuhan Univ Technol, Dept Informat Engn, Wuhan 430070, Peoples R China

来源：

DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2005年 / 2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：

In this paper, the proportional (P) neuron, integral (1) neuron and derivative (D) neuron are introduced and a new kind of neural network, PID neural network (PIDNN), is built. PIDNN has perfect performances for the control and decouple of the strong coupled multivariable time-varying systems. The paper displays the simulation results of the PIDNN system.

引用

页码：822 / 824

页数：3

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