{"title":"Adaptive discrete-time fuzzy sliding mode control for anti-lock braking systems","authors":"K. Emami, M. Akbarzadeh-T.","doi":"10.1109/NAFIPS.2003.1226807","DOIUrl":null,"url":null,"abstract":"A discrete-time adaptive fuzzy sliding mode controller is proposed for an antilock braking system (ABS) of a 13th order two-wheel nonlinear model of a car. The model includes interaction of front and rear wheel subsystems. The presented controller aims to least depend on a mathematical model, only assuming certain upper and lower bounds of uncertainties. The controller is designed based on a hybrid combination of variable structure control, direct adaptive fuzzy control and linear control. Two fuzzy approximators are used to estimate nonlinear functions of the plant. The controller is global uniform Lyapunov stable. Simulation results show favorable output tracking performance despite poor knowledge of wheel dynamics and system disturbances such as road roughness.","PeriodicalId":153530,"journal":{"name":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2003.1226807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
A discrete-time adaptive fuzzy sliding mode controller is proposed for an antilock braking system (ABS) of a 13th order two-wheel nonlinear model of a car. The model includes interaction of front and rear wheel subsystems. The presented controller aims to least depend on a mathematical model, only assuming certain upper and lower bounds of uncertainties. The controller is designed based on a hybrid combination of variable structure control, direct adaptive fuzzy control and linear control. Two fuzzy approximators are used to estimate nonlinear functions of the plant. The controller is global uniform Lyapunov stable. Simulation results show favorable output tracking performance despite poor knowledge of wheel dynamics and system disturbances such as road roughness.
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