{"title":"基于神经网络逼近的动态抓取系统控制","authors":"G. Guo, W. Gruver, K. Jin","doi":"10.1109/ISIC.1991.187357","DOIUrl":null,"url":null,"abstract":"A control algorithm for dynamic grasping systems using neural network approximation (NNA) is proposed. The kinematic and dynamic equations of the grasping system are derived. Based on these equations, a method for generalized computed torque control is developed. From computations of this control scheme, four elemental operation functions that are realized by elemental NNA functions are induced. All of the control computations in the grasping system are accomplished using neural network approximation. The PD control of a two-jointed finger mechanism is studied as an example of the application of the algorithm. Results using the NNA functions are compared.<<ETX>>","PeriodicalId":140507,"journal":{"name":"Proceedings of the 1991 IEEE International Symposium on Intelligent Control","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Control of dynamic grasping systems using neural network approximation\",\"authors\":\"G. Guo, W. Gruver, K. Jin\",\"doi\":\"10.1109/ISIC.1991.187357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A control algorithm for dynamic grasping systems using neural network approximation (NNA) is proposed. The kinematic and dynamic equations of the grasping system are derived. Based on these equations, a method for generalized computed torque control is developed. From computations of this control scheme, four elemental operation functions that are realized by elemental NNA functions are induced. All of the control computations in the grasping system are accomplished using neural network approximation. The PD control of a two-jointed finger mechanism is studied as an example of the application of the algorithm. Results using the NNA functions are compared.<<ETX>>\",\"PeriodicalId\":140507,\"journal\":{\"name\":\"Proceedings of the 1991 IEEE International Symposium on Intelligent Control\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1991 IEEE International Symposium on Intelligent Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.1991.187357\",\"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 1991 IEEE International Symposium on Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.1991.187357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Control of dynamic grasping systems using neural network approximation
A control algorithm for dynamic grasping systems using neural network approximation (NNA) is proposed. The kinematic and dynamic equations of the grasping system are derived. Based on these equations, a method for generalized computed torque control is developed. From computations of this control scheme, four elemental operation functions that are realized by elemental NNA functions are induced. All of the control computations in the grasping system are accomplished using neural network approximation. The PD control of a two-jointed finger mechanism is studied as an example of the application of the algorithm. Results using the NNA functions are compared.<>
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