{"title":"A fuzzy compensated PID controller for formation control of mobile robots","authors":"K. Bae, Yong-Baek Kim, Young-Kiu Choi","doi":"10.1109/ICMIC.2014.7020739","DOIUrl":null,"url":null,"abstract":"In this paper, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. So a fuzzy compensator is added to improve control performance. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.","PeriodicalId":405363,"journal":{"name":"Proceedings of 2014 International Conference on Modelling, Identification & Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2014 International Conference on Modelling, Identification & Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMIC.2014.7020739","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, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. So a fuzzy compensator is added to improve control performance. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.