{"title":"Tuning of Auto-Disturbance Rejection Controller Based on the Invasive Weed Optimization","authors":"Zhihua Chen, Shuo Wang, Zhonghua Deng, Xuncai Zhang","doi":"10.1109/BIC-TA.2011.45","DOIUrl":null,"url":null,"abstract":"Auto-Disturbance Rejection Controller (ADRC) has been proved to be a capable replacement of PID with unmistakable advantage in performance and practicality. But it is difficult to obtain a set of optimal parameters, for ADRC controller has too many parameters and has no deterministic rules to compute the parameters. In this paper, Objective function is constructed based on the control system performance indexes. Combined with experienced parameters of ADRC, an invasive weed optimization algorithm (IWO) is employed to obtain a set of key parameters. The simulation results show the validity of the IWO algorithm.","PeriodicalId":211822,"journal":{"name":"2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIC-TA.2011.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Auto-Disturbance Rejection Controller (ADRC) has been proved to be a capable replacement of PID with unmistakable advantage in performance and practicality. But it is difficult to obtain a set of optimal parameters, for ADRC controller has too many parameters and has no deterministic rules to compute the parameters. In this paper, Objective function is constructed based on the control system performance indexes. Combined with experienced parameters of ADRC, an invasive weed optimization algorithm (IWO) is employed to obtain a set of key parameters. The simulation results show the validity of the IWO algorithm.
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