{"title":"基于模糊干扰估计的直驱机器人滑模控制","authors":"A. Rojko, K. Jezernik","doi":"10.1109/IECON.2001.976504","DOIUrl":null,"url":null,"abstract":"This paper presents a decoupled continuous sliding mode controller suitable for use in the motion control of uncertain nonlinear systems, as direct drive robots. A disturbance compensation problem is solved by a fuzzy logic system (FLS) with adaptive positions of output fuzzy membership functions. The stability of the adaptation procedure is given via the Lyapunov stability theorem. FLS is divided into three fuzzy subsystems according to the physical properties of robot dynamics. This structure results in a clear fuzzy rule base with a reduced number of rules and enables systematic inclusion of linguistic knowledge. Performance of the proposed method is illustrated by experimental results in a motion control task and positioning task with varying payload on a three degree of freedom direct drive robot.","PeriodicalId":345608,"journal":{"name":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Sliding mode control of direct drive robot using fuzzy disturbance estimation\",\"authors\":\"A. Rojko, K. Jezernik\",\"doi\":\"10.1109/IECON.2001.976504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a decoupled continuous sliding mode controller suitable for use in the motion control of uncertain nonlinear systems, as direct drive robots. A disturbance compensation problem is solved by a fuzzy logic system (FLS) with adaptive positions of output fuzzy membership functions. The stability of the adaptation procedure is given via the Lyapunov stability theorem. FLS is divided into three fuzzy subsystems according to the physical properties of robot dynamics. This structure results in a clear fuzzy rule base with a reduced number of rules and enables systematic inclusion of linguistic knowledge. Performance of the proposed method is illustrated by experimental results in a motion control task and positioning task with varying payload on a three degree of freedom direct drive robot.\",\"PeriodicalId\":345608,\"journal\":{\"name\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECON.2001.976504\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2001.976504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sliding mode control of direct drive robot using fuzzy disturbance estimation
This paper presents a decoupled continuous sliding mode controller suitable for use in the motion control of uncertain nonlinear systems, as direct drive robots. A disturbance compensation problem is solved by a fuzzy logic system (FLS) with adaptive positions of output fuzzy membership functions. The stability of the adaptation procedure is given via the Lyapunov stability theorem. FLS is divided into three fuzzy subsystems according to the physical properties of robot dynamics. This structure results in a clear fuzzy rule base with a reduced number of rules and enables systematic inclusion of linguistic knowledge. Performance of the proposed method is illustrated by experimental results in a motion control task and positioning task with varying payload on a three degree of freedom direct drive robot.