{"title":"基于神经网络的气动人工肌肉机器人手臂智能扭转滑模控制器","authors":"S. Boudoua, M. Hamerlain, F. Hamerlain","doi":"10.1109/RASM.2015.7154592","DOIUrl":null,"url":null,"abstract":"In this note we present a novel intelligent twisting sliding mode controller using neural network, achieving chatter reduction for the control of pneumatic artificial muscles robot arm. The system is highly non-linear and somehow difficult to model therefore resorting to robust control is required. Thanks to their property as universal approximators, in this work a two layer NN with on line adaptive learning law is used to reconstruct unknown and unmodeled robot dynamics, and the realisation of a two sliding mode is achieved through the design of a nonlinear sliding surface. The stability of the overall system is guaranteed by lyapunov method. Experimental results are presented and discussed.","PeriodicalId":297041,"journal":{"name":"2015 International Workshop on Recent Advances in Sliding Modes (RASM)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Intelligent twisting sliding mode controller using neural network for pneumatic artificial muscles robot arm\",\"authors\":\"S. Boudoua, M. Hamerlain, F. Hamerlain\",\"doi\":\"10.1109/RASM.2015.7154592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this note we present a novel intelligent twisting sliding mode controller using neural network, achieving chatter reduction for the control of pneumatic artificial muscles robot arm. The system is highly non-linear and somehow difficult to model therefore resorting to robust control is required. Thanks to their property as universal approximators, in this work a two layer NN with on line adaptive learning law is used to reconstruct unknown and unmodeled robot dynamics, and the realisation of a two sliding mode is achieved through the design of a nonlinear sliding surface. The stability of the overall system is guaranteed by lyapunov method. Experimental results are presented and discussed.\",\"PeriodicalId\":297041,\"journal\":{\"name\":\"2015 International Workshop on Recent Advances in Sliding Modes (RASM)\",\"volume\":\"07 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Workshop on Recent Advances in Sliding Modes (RASM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RASM.2015.7154592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Workshop on Recent Advances in Sliding Modes (RASM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RASM.2015.7154592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent twisting sliding mode controller using neural network for pneumatic artificial muscles robot arm
In this note we present a novel intelligent twisting sliding mode controller using neural network, achieving chatter reduction for the control of pneumatic artificial muscles robot arm. The system is highly non-linear and somehow difficult to model therefore resorting to robust control is required. Thanks to their property as universal approximators, in this work a two layer NN with on line adaptive learning law is used to reconstruct unknown and unmodeled robot dynamics, and the realisation of a two sliding mode is achieved through the design of a nonlinear sliding surface. The stability of the overall system is guaranteed by lyapunov method. Experimental results are presented and discussed.