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压电陶瓷执行器的类Hammerstein模型及其参数辨识

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压电陶瓷执行器的类Hammerstein模型及其参数辨识 第20卷
第9期
2012年9月
文章编号
1004924X(2012)09208708
光学精密工程
Optics and Precision Engineering
Vol,20
No. 9 Sep.2012
压电陶瓷执行器的类Hammerstein模型及
其参数辨识赖志林*,刘向东,耿

(北京理工大学自动化学院复杂系统智能控制与决策重点实验室,北京100081)
摘要:针对压电陶瓷执行器的迟滞非线性对压电陶瓷精密定位的影响,提出了应用类Hammerstein模型对压电陶瓷执行器进行建模的方法。建立了压电陶瓷执行器的遇滞模型并且描述其额率相关性。利用类Hammerstein模型把压电陶瓷执行器看成静态迟滞模型和动态二阶系统的申联,其中静态模型由分类排序的Preisach模型进行描述,二阶系统应用遗传算法辨识其参数,实验结果表明:加人二阶系统后,类Hammerstein模型对频率的相关性有较大增强,其误差相应地大幅降低,在800Hz时平均绝对误差为0.3392μm;而由Preisach建立的迟滞模型的误差随着频率的增大而大幅增大,在800Hz为0.8881μm。
调:压电陶瓷执行器达滞非线性;Hammerstein模型:参数博识


中图分类号:TN384;TP273.1
文献标识码:A
doi;10,3788/OPE,20122009.2087
Hammerstein-basedmodelofpiezoceramic
actuatoranditsidentification LAI Zhi-lin', LIU Xiang-dong, GENG Jie
(Key Laboratory for Intelligent Control&Decision of Compler Systems, School of Automatic,Beijing Institute of Technology,Beijing 10008l,China)
+Corresponding author,E-mail:lai@bit.edu.cn
Abstract: For the effect of hysteretic linearity of a picezoceramic actuator on nano-positioning system, a modeling method based on Hammerstein model was proposed, The Hammerstein-based model for the piezoceramic actuator was established and its frequency dependence was described. By using the Ham merstein model, the piezoceramic actuator was taken as a static hysteretic model couple with a dyamic second-order system, and the former was described by the Preisach model and the latter was identified by the genetic algorithm, The experimental results show that the frequency dependence of the Ham-merstein-based model is improved after adding the second order system, correspondingly, the error is decreased greatly. In 8oo Hz, the absolute average tracking error of the Hammerstein-based model is 0. 339 2 μm, which is less than that of the Preisach model in 0, 888 1 μm.
Key words: piezoceramic actuator; hysteresis nonlinearity; Hammerstein model; parameter identification
收稿日期:2012-04-01;修订日期:2012-05-14.
基金项目:国家自然科学基金资助项目(No.10872030),国家重点基础研究发展计划(973计划)资助项目(No.
2012CB720000);北京市自然科学基金资助项目(No.4122066)
上一章:神经信息实时处理平台的快速开发 下一章:压电陶瓷驱动器的滑模神经网络控制

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