{"title":"气动肌肉执行器的模糊自适应内模控制","authors":"Xiong Zhang, Jiwei Hu, Zemin Liu","doi":"10.1145/3318299.3318360","DOIUrl":null,"url":null,"abstract":"Pneumatic muscle actuator is difficult to model and has strong nonlinear and time-varying properties. In this paper, to control a pneumatic muscle actuator a fuzzy adaptive internal model control algorithm (FAIMC) is proposed by combining internal model control and fuzzy control. The FAIMC controller includes a fuzzy inverse internal model controller and a filter. Both the fuzzy model and the inverse model of the process are obtained by T-S fuzzy model identification, and the filter parameters are adjusted online by fuzzy logic. Through the matlab simulation and the experimental platform of the pneumatic muscle actuator, the results show that the FAIMC algorithm can effectively control the pneumatic muscle actuator.","PeriodicalId":164987,"journal":{"name":"International Conference on Machine Learning and Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy Adaptive Internal Model Control for a Pneumatic Muscle Actuator\",\"authors\":\"Xiong Zhang, Jiwei Hu, Zemin Liu\",\"doi\":\"10.1145/3318299.3318360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pneumatic muscle actuator is difficult to model and has strong nonlinear and time-varying properties. In this paper, to control a pneumatic muscle actuator a fuzzy adaptive internal model control algorithm (FAIMC) is proposed by combining internal model control and fuzzy control. The FAIMC controller includes a fuzzy inverse internal model controller and a filter. Both the fuzzy model and the inverse model of the process are obtained by T-S fuzzy model identification, and the filter parameters are adjusted online by fuzzy logic. Through the matlab simulation and the experimental platform of the pneumatic muscle actuator, the results show that the FAIMC algorithm can effectively control the pneumatic muscle actuator.\",\"PeriodicalId\":164987,\"journal\":{\"name\":\"International Conference on Machine Learning and Computing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3318299.3318360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318299.3318360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy Adaptive Internal Model Control for a Pneumatic Muscle Actuator
Pneumatic muscle actuator is difficult to model and has strong nonlinear and time-varying properties. In this paper, to control a pneumatic muscle actuator a fuzzy adaptive internal model control algorithm (FAIMC) is proposed by combining internal model control and fuzzy control. The FAIMC controller includes a fuzzy inverse internal model controller and a filter. Both the fuzzy model and the inverse model of the process are obtained by T-S fuzzy model identification, and the filter parameters are adjusted online by fuzzy logic. Through the matlab simulation and the experimental platform of the pneumatic muscle actuator, the results show that the FAIMC algorithm can effectively control the pneumatic muscle actuator.
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