Application of RBF neural network and sliding mode control for a servo mechanical press

被引：0
|
作者：
Liu, Chen [1 ]
Zhao, Sheng-dun [1 ]
机构：
[1] Xi An Jiao Tong Univ, Xian 710049, Shaanxi, Peoples R China
来源：
2016 IEEE/CSAA INTERNATIONAL CONFERENCE ON AIRCRAFT UTILITY SYSTEMS (AUS) | 2016年
关键词：
FRICTION;
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
Servo mechanical press is a complicated system with several transmission processes. The friction and other nonlinear factors are critical problems of servo press controlling. This paper focuses on the performance improvements of position tracking on servo press. In order to carry out the researches, first, the mathematic model which expresses the mechanical transmission processes is built to analyze the servo screw press system. Then an algorithm which combined neural network and fuzzy sliding mode (RBFFS) was proposed and applied on the position tracking of servo press. Finally, the simulation and experiment results indicate that the RBFFS control algorithm is effective and capable for servo press controlling.
引用
收藏
页码：346 / 351
页数：6
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