{"title":"气动肌肉执行器模拟退火整定模糊自适应控制","authors":"A. Hošovský, P. Michał, M. Tóthová, O. Biros","doi":"10.1109/SAMI.2014.6822408","DOIUrl":null,"url":null,"abstract":"Pneumatic artificial muscles - based robotic systems usually necessitate the use various nonlinear control techniques in order to improve their performance. Moreover, their robustness to parameter variation, which is generally hardly predictable, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of PD controller under conditions of inertia moment variation. The design of fuzzy controller is based on the results of optimization using simulated annealing algorithm. The results confirm fast action of the control scheme as well as its robustness to changes in inertia moment variation.","PeriodicalId":441172,"journal":{"name":"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Fuzzy adaptive control for pneumatic muscle actuator with simulated annealing tuning\",\"authors\":\"A. Hošovský, P. Michał, M. Tóthová, O. Biros\",\"doi\":\"10.1109/SAMI.2014.6822408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pneumatic artificial muscles - based robotic systems usually necessitate the use various nonlinear control techniques in order to improve their performance. Moreover, their robustness to parameter variation, which is generally hardly predictable, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of PD controller under conditions of inertia moment variation. The design of fuzzy controller is based on the results of optimization using simulated annealing algorithm. The results confirm fast action of the control scheme as well as its robustness to changes in inertia moment variation.\",\"PeriodicalId\":441172,\"journal\":{\"name\":\"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2014.6822408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2014.6822408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy adaptive control for pneumatic muscle actuator with simulated annealing tuning
Pneumatic artificial muscles - based robotic systems usually necessitate the use various nonlinear control techniques in order to improve their performance. Moreover, their robustness to parameter variation, which is generally hardly predictable, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of PD controller under conditions of inertia moment variation. The design of fuzzy controller is based on the results of optimization using simulated annealing algorithm. The results confirm fast action of the control scheme as well as its robustness to changes in inertia moment variation.