Backlash Nonlinear Compensation of Servo Systems Using Backpropagation Neural Networks

作     者：何超 徐立新 张宇河 He Chao;Xu Lixin;Zhang Yuhe

作者机构：北京理工大学自动控制系北京100081 

出 版 物：《Journal of Beijing Institute of Technology》 (北京理工大学学报（英文版）)

年 卷 期：1999年第8卷第3期

页      码：300-305页

摘      要：Aim To eliminate the influences of backlash nonlinear characteristics generally existing in servo systems, a nonlinear compensation method using backpropagation neural networks(BPNN) is presented. Methods Based on some weapon tracking servo system, a three layer BPNN was used to off line identify the backlash characteristics, then a nonlinear compensator was designed according to the identification results. Results The simulation results show that the method can effectively get rid of the sustained oscillation(limit cycle) of the system caused by the backlash characteristics, and can improve the system accuracy. Conclusion The method is effective on sloving the problems produced by the backlash characteristics in servo systems, and it can be easily accomplished in engineering.

主 题 词：servo system backlash nonlinear characteristics limit cycle backpropagation neural networks(BPNN) compensation methods 

学科分类：08[工学] 0835[0835] 0802[工学-机械学] 080201[080201] 

D　O　I：10.3969/j.issn.1004-0579.1999.03.013

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