Zipeng Xu, Longlong Fan, Yongli Zhang, Hongxing Li
{"title":"Obstacle avoidance control of the unmanned bicycle based on variable universe fuzzy exponential rate reaching law sliding mode control","authors":"Zipeng Xu, Longlong Fan, Yongli Zhang, Hongxing Li","doi":"10.1109/ICCSS53909.2021.9721977","DOIUrl":null,"url":null,"abstract":"In this paper, a variable universe fuzzy exponential rate reaching law sliding mode controller (VFSMC) is designed for obstacle avoidance and stabilization of the unmanned bicycle. First, a variable universe fuzzy controller is used to adjust the parameter of the sliding mode controller. Then, a fuzzy controller is considered to realize the error correction of the sliding mode controller to improve the accuracy of the controller. Further, the artificial potential field method is adopted to achieve obstacle avoidance control of the unmanned bicycle. Some numerical simulations are provided to illustrate the validity of the proposed controller.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"13 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSS53909.2021.9721977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a variable universe fuzzy exponential rate reaching law sliding mode controller (VFSMC) is designed for obstacle avoidance and stabilization of the unmanned bicycle. First, a variable universe fuzzy controller is used to adjust the parameter of the sliding mode controller. Then, a fuzzy controller is considered to realize the error correction of the sliding mode controller to improve the accuracy of the controller. Further, the artificial potential field method is adopted to achieve obstacle avoidance control of the unmanned bicycle. Some numerical simulations are provided to illustrate the validity of the proposed controller.