{"title":"基于分布参数的柔性载荷机械手反步控制","authors":"Zhiguo Tang, Yuan-chun Li","doi":"10.1109/ICMA.2010.22","DOIUrl":null,"url":null,"abstract":"In the paper, the distributed parameter dynamic model for the system was proposed by Hamilton’s principle aimed at multivariable rigid-flexible coupling system of a dual-manipulator cooperative system handling a flexible payload. Then considering the complexity of the dynamic model, the obtained model was divided into two subsystems which include a slow lumped subsystem describing the large rigid motion and a fast distributed subsystem expressing the elastic vibration based on singular perturbation theory. The robust neural network controller was studied based on back stepping in the slow subsystem, which can complete system trajectory tracking performance. For the fast subsystem, a sliding mode controller was presented to suppress the elastic vibration of the system. Simulation results show that the proposed controller can strengthen the tracing ability and robustness of the system.","PeriodicalId":233469,"journal":{"name":"2010 International Conference on Manufacturing Automation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Backstepping Control of Manipulators Handling a Flexible Payload Based on Distributed Parameter\",\"authors\":\"Zhiguo Tang, Yuan-chun Li\",\"doi\":\"10.1109/ICMA.2010.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper, the distributed parameter dynamic model for the system was proposed by Hamilton’s principle aimed at multivariable rigid-flexible coupling system of a dual-manipulator cooperative system handling a flexible payload. Then considering the complexity of the dynamic model, the obtained model was divided into two subsystems which include a slow lumped subsystem describing the large rigid motion and a fast distributed subsystem expressing the elastic vibration based on singular perturbation theory. The robust neural network controller was studied based on back stepping in the slow subsystem, which can complete system trajectory tracking performance. For the fast subsystem, a sliding mode controller was presented to suppress the elastic vibration of the system. Simulation results show that the proposed controller can strengthen the tracing ability and robustness of the system.\",\"PeriodicalId\":233469,\"journal\":{\"name\":\"2010 International Conference on Manufacturing Automation\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Manufacturing Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2010.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Manufacturing Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2010.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Backstepping Control of Manipulators Handling a Flexible Payload Based on Distributed Parameter
In the paper, the distributed parameter dynamic model for the system was proposed by Hamilton’s principle aimed at multivariable rigid-flexible coupling system of a dual-manipulator cooperative system handling a flexible payload. Then considering the complexity of the dynamic model, the obtained model was divided into two subsystems which include a slow lumped subsystem describing the large rigid motion and a fast distributed subsystem expressing the elastic vibration based on singular perturbation theory. The robust neural network controller was studied based on back stepping in the slow subsystem, which can complete system trajectory tracking performance. For the fast subsystem, a sliding mode controller was presented to suppress the elastic vibration of the system. Simulation results show that the proposed controller can strengthen the tracing ability and robustness of the system.