{"title":"基于粒子群优化的机械臂参数辨识","authors":"N. Mizuno, Canh Son Nguyen","doi":"10.1109/ICCA.2017.8003078","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate identification methods for dynamic parameters of robot manipulator. The focused method is based on heuristic particle swarm optimization algorithm (PSO) with some extended features. The estimated parameters by PSO are used to predict required joint torques for high accuracy tracking control. The effectiveness of some PSO methods for tracking control problem are verified by cross-validation with data set produced by several trajectories.","PeriodicalId":379025,"journal":{"name":"2017 13th IEEE International Conference on Control & Automation (ICCA)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Parameters identification of robot manipulator based on particle swarm optimization\",\"authors\":\"N. Mizuno, Canh Son Nguyen\",\"doi\":\"10.1109/ICCA.2017.8003078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate identification methods for dynamic parameters of robot manipulator. The focused method is based on heuristic particle swarm optimization algorithm (PSO) with some extended features. The estimated parameters by PSO are used to predict required joint torques for high accuracy tracking control. The effectiveness of some PSO methods for tracking control problem are verified by cross-validation with data set produced by several trajectories.\",\"PeriodicalId\":379025,\"journal\":{\"name\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"volume\":\"141 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2017.8003078\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE International Conference on Control & Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2017.8003078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parameters identification of robot manipulator based on particle swarm optimization
In this paper, we investigate identification methods for dynamic parameters of robot manipulator. The focused method is based on heuristic particle swarm optimization algorithm (PSO) with some extended features. The estimated parameters by PSO are used to predict required joint torques for high accuracy tracking control. The effectiveness of some PSO methods for tracking control problem are verified by cross-validation with data set produced by several trajectories.
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