{"title":"一种新型遥控机器人双模自适应模糊控制","authors":"Jing Zhang, Heng Wang, Shiyin Jiang","doi":"10.1109/CCIENG.2011.6008078","DOIUrl":null,"url":null,"abstract":"In this paper, an dynamics model is established for telerobot. Based on the dynamics model, the authors design a new dual-mode adaptive fuzzy control system and use Lyapunov stability theory to prove the stability of the system and the boundness of tracking error. In order to improve robustness, the dual-mode adaptive fuzzy controller is modified and equipped with self-adjusting and new switching. The simulation results show that this dual-mode adaptive fuzzy control system has excellent control effect. Namely the controller can effectively overcome the unknown parameters of the model and environmental disturbances. It also shows that the proposed method has strong adaptive ability, fast dynamic response, strong robustness and applicability.","PeriodicalId":6316,"journal":{"name":"2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering","volume":"46 1","pages":"106-110"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new dual-mode adaptive fuzzy control of telerobot\",\"authors\":\"Jing Zhang, Heng Wang, Shiyin Jiang\",\"doi\":\"10.1109/CCIENG.2011.6008078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an dynamics model is established for telerobot. Based on the dynamics model, the authors design a new dual-mode adaptive fuzzy control system and use Lyapunov stability theory to prove the stability of the system and the boundness of tracking error. In order to improve robustness, the dual-mode adaptive fuzzy controller is modified and equipped with self-adjusting and new switching. The simulation results show that this dual-mode adaptive fuzzy control system has excellent control effect. Namely the controller can effectively overcome the unknown parameters of the model and environmental disturbances. It also shows that the proposed method has strong adaptive ability, fast dynamic response, strong robustness and applicability.\",\"PeriodicalId\":6316,\"journal\":{\"name\":\"2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering\",\"volume\":\"46 1\",\"pages\":\"106-110\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCIENG.2011.6008078\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIENG.2011.6008078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new dual-mode adaptive fuzzy control of telerobot
In this paper, an dynamics model is established for telerobot. Based on the dynamics model, the authors design a new dual-mode adaptive fuzzy control system and use Lyapunov stability theory to prove the stability of the system and the boundness of tracking error. In order to improve robustness, the dual-mode adaptive fuzzy controller is modified and equipped with self-adjusting and new switching. The simulation results show that this dual-mode adaptive fuzzy control system has excellent control effect. Namely the controller can effectively overcome the unknown parameters of the model and environmental disturbances. It also shows that the proposed method has strong adaptive ability, fast dynamic response, strong robustness and applicability.