{"title":"Self-tuning type variable structure control method for a class of nonlinear systems","authors":"Jian-xin Xu, Tong-heng Lee, Mao Wang","doi":"10.1109/VSS.1996.578547","DOIUrl":null,"url":null,"abstract":"In this paper we propose a new self-tuning type variable structure control (VSC) method for a class of nonlinear dynamical systems with parametric uncertainties. The control law is designed to satisfy the sliding mode condition while the online parameter identification is incorporated in the control system. Necessary modifications are made for the parameter identification to avoid the singularity of control input. By virtue of sliding mode, the proposed identification algorithm can be applied to those nonlinear systems which may not be linear in parametric space but are linear while in sliding mode. A model-based strategy is further introduced to estimate the uncertainty bound. The new approach attains the gain scheduling property by tuning the switching gain in accordance with the estimated system uncertainties, that is, the switching gain tends to reduce asymptotically while ensuring that the sliding mode condition is maintained.","PeriodicalId":393072,"journal":{"name":"Proceedings. 1996 IEEE International Workshop on Variable Structure Systems. - VSS'96 -","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1996 IEEE International Workshop on Variable Structure Systems. - VSS'96 -","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VSS.1996.578547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper we propose a new self-tuning type variable structure control (VSC) method for a class of nonlinear dynamical systems with parametric uncertainties. The control law is designed to satisfy the sliding mode condition while the online parameter identification is incorporated in the control system. Necessary modifications are made for the parameter identification to avoid the singularity of control input. By virtue of sliding mode, the proposed identification algorithm can be applied to those nonlinear systems which may not be linear in parametric space but are linear while in sliding mode. A model-based strategy is further introduced to estimate the uncertainty bound. The new approach attains the gain scheduling property by tuning the switching gain in accordance with the estimated system uncertainties, that is, the switching gain tends to reduce asymptotically while ensuring that the sliding mode condition is maintained.