{"title":"An adaptive fuzzy-neural control approach for vehicle lateral dynamics","authors":"Chen-Sheng Ting, Chuan-Sheng Liu","doi":"10.1109/ICSAI.2012.6223089","DOIUrl":null,"url":null,"abstract":"This study addresses an adaptive backstepping fuzzy control approach for automatic steering vehicles. The vehicle lateral dynamics is presented by an eight degree-of-freedom model, which considers the nonlinear behaviors such as tire force, wheel rotations, forward velocity, and roll motion. According to the existing result, the analysis and design on this model is difficult to perform because of its model complexity. To facilitate the designing work, a robust control scheme which is based on T-S fuzzy control strategy is investigated. The stability condition for ensuring that the control system is uniformly ultimately bounded is derived based on Lyapunov's method. Finally, the effectiveness of the proposed approach is verified via numeric examples.","PeriodicalId":164945,"journal":{"name":"2012 International Conference on Systems and Informatics (ICSAI2012)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Systems and Informatics (ICSAI2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2012.6223089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This study addresses an adaptive backstepping fuzzy control approach for automatic steering vehicles. The vehicle lateral dynamics is presented by an eight degree-of-freedom model, which considers the nonlinear behaviors such as tire force, wheel rotations, forward velocity, and roll motion. According to the existing result, the analysis and design on this model is difficult to perform because of its model complexity. To facilitate the designing work, a robust control scheme which is based on T-S fuzzy control strategy is investigated. The stability condition for ensuring that the control system is uniformly ultimately bounded is derived based on Lyapunov's method. Finally, the effectiveness of the proposed approach is verified via numeric examples.