{"title":"基于ESO的机器人轨迹跟踪鲁棒自适应方法","authors":"Dazi Li, Jiang Wang","doi":"10.1109/ICCA.2019.8899737","DOIUrl":null,"url":null,"abstract":"Due to the strong nonlinearity, coupling and unknown external disturbances of the robot system, the problem of high precision trajectory tracking control of robot is always difficult to solve. Therefore, a robust adaptive trajectory tracking method based on extended state observer (ESO) is proposed in this paper. Extended state observer can estimate the sum of the internal and external disturbances, that is, the total disturbances of the system, and compensate it to achieve high precision tracking of the robot trajectory. Robust adaptive algorithm has good self-adjustability to the structural parameters of the robot system, so the robustness of the controller can be guaranteed. Simulation results show that the proposed method has good tracking performance and anti-interference performance.","PeriodicalId":130891,"journal":{"name":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Robust Adaptive Method Based on ESO for Trajectory Tracking of Robot Manipulator\",\"authors\":\"Dazi Li, Jiang Wang\",\"doi\":\"10.1109/ICCA.2019.8899737\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the strong nonlinearity, coupling and unknown external disturbances of the robot system, the problem of high precision trajectory tracking control of robot is always difficult to solve. Therefore, a robust adaptive trajectory tracking method based on extended state observer (ESO) is proposed in this paper. Extended state observer can estimate the sum of the internal and external disturbances, that is, the total disturbances of the system, and compensate it to achieve high precision tracking of the robot trajectory. Robust adaptive algorithm has good self-adjustability to the structural parameters of the robot system, so the robustness of the controller can be guaranteed. Simulation results show that the proposed method has good tracking performance and anti-interference performance.\",\"PeriodicalId\":130891,\"journal\":{\"name\":\"2019 IEEE 15th International Conference on Control and Automation (ICCA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 15th International Conference on Control and Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2019.8899737\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2019.8899737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Robust Adaptive Method Based on ESO for Trajectory Tracking of Robot Manipulator
Due to the strong nonlinearity, coupling and unknown external disturbances of the robot system, the problem of high precision trajectory tracking control of robot is always difficult to solve. Therefore, a robust adaptive trajectory tracking method based on extended state observer (ESO) is proposed in this paper. Extended state observer can estimate the sum of the internal and external disturbances, that is, the total disturbances of the system, and compensate it to achieve high precision tracking of the robot trajectory. Robust adaptive algorithm has good self-adjustability to the structural parameters of the robot system, so the robustness of the controller can be guaranteed. Simulation results show that the proposed method has good tracking performance and anti-interference performance.