{"title":"LMS adaptive fuzzy control for vehicle active suspension system","authors":"Jianmin Sun, Qingmei Yang, Yuewu Dong, Yi Zhang","doi":"10.1109/ITSC.2003.1252708","DOIUrl":null,"url":null,"abstract":"The riding comfort and handling safety of vehicle are regarded as control aims. With the nonlinearity of the road-vehicle system, an adjustable fuzzy control algorithm, whose fuzzy control rule table can be obtained with the numerical calculation is put forward. Because the algorithm can adjust the rectification factor of fuzzy controller with the least means squares (LMS) method, it can reflect the advantage of fuzzy logic in nonlinearity systems and also can improve the disadvantage of common fuzzy control method strongly depending on the experience. For two degree-of freedom (DOF) vehicle model, the simulation of vehicle performance in road signal is studied, its results show the adjustable fuzzy controller can reduce the acceleration of the sprung mass by a factor of 20. According to the experiment study of vehicle model, the results further prove that the algorithm can effectively control the vibration of the vehicle system.","PeriodicalId":123155,"journal":{"name":"Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2003.1252708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The riding comfort and handling safety of vehicle are regarded as control aims. With the nonlinearity of the road-vehicle system, an adjustable fuzzy control algorithm, whose fuzzy control rule table can be obtained with the numerical calculation is put forward. Because the algorithm can adjust the rectification factor of fuzzy controller with the least means squares (LMS) method, it can reflect the advantage of fuzzy logic in nonlinearity systems and also can improve the disadvantage of common fuzzy control method strongly depending on the experience. For two degree-of freedom (DOF) vehicle model, the simulation of vehicle performance in road signal is studied, its results show the adjustable fuzzy controller can reduce the acceleration of the sprung mass by a factor of 20. According to the experiment study of vehicle model, the results further prove that the algorithm can effectively control the vibration of the vehicle system.
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