{"title":"On the performance of improved extended state observer based control for uncertain systems with measurement noises","authors":"Yuying Guo, Youmin Zhang","doi":"10.1109/CCDC.2017.7978458","DOIUrl":null,"url":null,"abstract":"This paper investigates a new framework of extended state observer (ESO) based active disturbance rejection control (ADRC) design methodology for a class of uncertain nonlinear systems subject to measurement noises. First, based on nonlinear filtering function, an improved ESO is designed to estimate both state, and total disturbance which includes the internal uncertain nonlinear part and the external uncertain disturbance. Then, the explicit analysis about how to select nonlinear filtering function and the convergence analysis for the error dynamics are presented. Numerical simulation results are shown to demonstrate the effectiveness of the proposed method.","PeriodicalId":6588,"journal":{"name":"2017 29th Chinese Control And Decision Conference (CCDC)","volume":"10 1","pages":"7072-7077"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 29th Chinese Control And Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2017.7978458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the performance of improved extended state observer based control for uncertain systems with measurement noises
This paper investigates a new framework of extended state observer (ESO) based active disturbance rejection control (ADRC) design methodology for a class of uncertain nonlinear systems subject to measurement noises. First, based on nonlinear filtering function, an improved ESO is designed to estimate both state, and total disturbance which includes the internal uncertain nonlinear part and the external uncertain disturbance. Then, the explicit analysis about how to select nonlinear filtering function and the convergence analysis for the error dynamics are presented. Numerical simulation results are shown to demonstrate the effectiveness of the proposed method.