PID Neural Network Decoupling Control of Multi-variable System and its Application

被引：0
|
作者：
Yu, DongJiang [1 ]
Long, WeiZhi [2 ]
He, JiaBing [2 ]
机构：
[1] Datang Power Generat Grp, Hunan Branch, Changsha 410011, Hunan, Peoples R China
[2] Datang Huayin Youxian Energy Corp Ltd, Luoyang 412307, Peoples R China
来源：
PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INFORMATION ENGINEERING FOR MECHANICS AND MATERIALS | 2016年 / 97卷
关键词：
MPIDNN; Decoupling Control; Multi-variable; Simulation;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this thesis, multi-output PID neural network (MPIDNN) is proposed based on the research on single-output PID and it is simulated. MPIDNN is also proposed for the characteristics of coupling system which is difficult to control in industrial process. The results of the simulation show that the control algorithm has the function of online learning to adjust parameters. For multi-input and multi-output system, by using the MPIDNN decoupling control method, there is no need to get the exact model of object. It can offset the effects of the internal model or other disturbance and achieve better control effect.
引用
收藏
页码：277 / 282
页数：6
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