The model-free learning enhanced motion control of DC motor

被引：0
|
作者：
Cao, Rongmin [1 ]
Hou, Zhongsheng [2 ]
Zhang, Wei [1 ]
机构：
[1] Beijing Inst Machinery Ind, Dept Comp & Automat, Beijing, Peoples R China
[2] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
来源：
2007 INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS, VOLS 1-4 | 2007年
关键词：
ILC; computer simulation; DC motor; MFLAC; nonlinear systems; stability;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents an approach towards learning enhanced motion control of DC motor, suitable for applications involving repeated iterations of motion trajectories. The overall structure of the control consists of a feedback and a feed-forward components. The model-free learning adaptive feedback control (MFLAC) provides for the main system stabilization and an iterative learning control (ILC) algorithm is proposed to serve as a feedforward compensation to nonlinear and unknown dynamics and disturbances, thereby enhancing the improvement achievable with PID or MFLAC alone. It serves as the basis for simulation study of the proposed control scheme. A comparison of the performance achieved with traditional PID and MFLAC is also provided to highlight the advantages of the additional intelligent feedforward mode.
引用
收藏
页码：1268 / +
页数：2
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