Modeling of Ultra-precision Positioning System driven by Piezoelectric Actuator

摘要：

　　A neural network based approach for the identification of the rate-dependent hysteresis in the piezoelectric actuators is proposed in this article.In this method,a dynamic hysteresis operator for expanded input space is proposed to extract the change-tendency and rate-dependency of the dynamic hysteresis,the parameters of the hysteretic operator is identified using genetic algorithm.An expanded input space involving the original input variable and the new operator is constructed.Thus,based on the expanded input space,the neural networks can be utilized to approximate the behavior of the rate-dependent hysteresis.Furthermore,the dynamic performance of the model is improved because of the existence of dynamic operator.Finally,the method is used to the modeling of hysteresis in a piezoelectric actuator,the experimental results are presented to verify the effectiveness of the proposed approach.

关键词： Hysteresis hysteretic operator genetic algorithm neural networks

作者: Chen Hui Tan Yong-hong Zhou Xing-peng Zhang Ya-hong Dong Rui-li

作者单位: School of Automation, Southeast University, Nanjing 210096, China;School of Electronic Engineering & College of Information, Mechanical and Electrical Engineering, Shanghai NormalUniversity,Shanghai 20 School of Automation, Southeast University, Nanjing 210096, China Department of Computer Science and Technology, Guilin University of Aerospace Technology,Guilin, 541

会议类型: 国际会议

会议名称: 中国微米纳米技术学会第14届学术年会、第3届国际年会暨第6届微米纳米技术“创新与产业化国际研讨与展览会(CSMNT2012 & ICMAN2012)

会议地点: 杭州

会议语种:英文

页码: 1-6

在线出版日期: 2012-11-04（万方平台首次上网日期，不代表论文的发表时间）