{"title":"A robust extended Kalman filter for modeling piezoelectric actuators","authors":"N. Chuang","doi":"10.1109/ACC.2016.7526071","DOIUrl":null,"url":null,"abstract":"This paper presents an improved hysteretic model for a piezoelectric actuator (PEA) based nano-positioning system. PEAs exhibit hysteresis nonlinearities, which can dramatically limit control performance and accuracy of the nano-positioning system. The paper provides a design of a hysteretic nonlinearity estimator using a robust extended Kalman filter to determine the best estimate for the hysteresis model. A good quality and an accurate level of the model is an important task and a prerequisite that may significantly affect the control performance in nano-positioning systems even using an advanced controller. With the respect to the hysteresis model considered in [1], the proposed approach in this paper demonstrates a significant improvement to have perfectly matched the experimental data of the measured hysteresis curve of the displacement by comparing the one presented in [1].","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2016.7526071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents an improved hysteretic model for a piezoelectric actuator (PEA) based nano-positioning system. PEAs exhibit hysteresis nonlinearities, which can dramatically limit control performance and accuracy of the nano-positioning system. The paper provides a design of a hysteretic nonlinearity estimator using a robust extended Kalman filter to determine the best estimate for the hysteresis model. A good quality and an accurate level of the model is an important task and a prerequisite that may significantly affect the control performance in nano-positioning systems even using an advanced controller. With the respect to the hysteresis model considered in [1], the proposed approach in this paper demonstrates a significant improvement to have perfectly matched the experimental data of the measured hysteresis curve of the displacement by comparing the one presented in [1].