{"title":"Tracking Control for Uncertain Chaotic Systems","authors":"Yu-ye Wang, Chun-xia Han","doi":"10.1109/ICCEE.2008.162","DOIUrl":null,"url":null,"abstract":"In this paper, a novel robust controller based on Lyapunov stability theory is introduced. This controller can achieve the tracking control of a class of chaotic systems with time-varying unknown parameters. Without complex algorithms, this robust controller is achieved by adjusting the robust factor. By adjusting the robust factor, the controller can be applied to different chaotic systems with different uncertainties. By increasing or decreasing the robust factorpsilas weight, the controller can perform different robustness. Increasing the robust factor, the proposed controller can stand larger uncertainties of the parameters, and can track the desired orbit more quickly. So the structure of the controller is flexible, it can be easily adjusted for different applications. Simulation results with Rossler and Liu system ver.ify the controller's effectiveness.","PeriodicalId":365473,"journal":{"name":"2008 International Conference on Computer and Electrical Engineering","volume":"495 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Computer and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEE.2008.162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, a novel robust controller based on Lyapunov stability theory is introduced. This controller can achieve the tracking control of a class of chaotic systems with time-varying unknown parameters. Without complex algorithms, this robust controller is achieved by adjusting the robust factor. By adjusting the robust factor, the controller can be applied to different chaotic systems with different uncertainties. By increasing or decreasing the robust factorpsilas weight, the controller can perform different robustness. Increasing the robust factor, the proposed controller can stand larger uncertainties of the parameters, and can track the desired orbit more quickly. So the structure of the controller is flexible, it can be easily adjusted for different applications. Simulation results with Rossler and Liu system ver.ify the controller's effectiveness.