{"title":"基于动态神经网络的双连杆机械臂自适应控制","authors":"Wen Yu, A. Poznyak, Encarna Sosa Sánchez","doi":"10.1109/ACC.1999.786507","DOIUrl":null,"url":null,"abstract":"A neurocontrol method for robot manipulators is presented. A single-layer dynamic neural network is used to estimate the unknown manipulators, then a direct linearization controller is derived based on the neuro identifier. Because the approximation capability is limited, another PD-like controller is applied to compensate the unmodeled dynamics. The main contribution of the paper is that the boundness of the identification error and tracking error are established.","PeriodicalId":441363,"journal":{"name":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Adaptive control of two-link manipulator via dynamic neural network\",\"authors\":\"Wen Yu, A. Poznyak, Encarna Sosa Sánchez\",\"doi\":\"10.1109/ACC.1999.786507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A neurocontrol method for robot manipulators is presented. A single-layer dynamic neural network is used to estimate the unknown manipulators, then a direct linearization controller is derived based on the neuro identifier. Because the approximation capability is limited, another PD-like controller is applied to compensate the unmodeled dynamics. The main contribution of the paper is that the boundness of the identification error and tracking error are established.\",\"PeriodicalId\":441363,\"journal\":{\"name\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.1999.786507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.1999.786507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive control of two-link manipulator via dynamic neural network
A neurocontrol method for robot manipulators is presented. A single-layer dynamic neural network is used to estimate the unknown manipulators, then a direct linearization controller is derived based on the neuro identifier. Because the approximation capability is limited, another PD-like controller is applied to compensate the unmodeled dynamics. The main contribution of the paper is that the boundness of the identification error and tracking error are established.
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