{"title":"基于神经网络的双连杆机器人控制器","authors":"M. Jamshidi, B. Horne, N. Vadiee","doi":"10.1109/CDC.1990.203395","DOIUrl":null,"url":null,"abstract":"A case of a multilayer perceptron (MLP) used for position control of a two-link robot is reported. Simulation results as well as the computational burden on neurocontrollers designed for robot control are presented. Such issues as the number of layers and number of nodes per layer are discussed. It is concluded that a neural network can be used to approximate a dynamical model of a robot. However, the error associated with this model is not nearly as good as that of conventional controllers, specifically a computed torque controller.<<ETX>>","PeriodicalId":287089,"journal":{"name":"29th IEEE Conference on Decision and Control","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A neural network-based controller for a two-link robot\",\"authors\":\"M. Jamshidi, B. Horne, N. Vadiee\",\"doi\":\"10.1109/CDC.1990.203395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A case of a multilayer perceptron (MLP) used for position control of a two-link robot is reported. Simulation results as well as the computational burden on neurocontrollers designed for robot control are presented. Such issues as the number of layers and number of nodes per layer are discussed. It is concluded that a neural network can be used to approximate a dynamical model of a robot. However, the error associated with this model is not nearly as good as that of conventional controllers, specifically a computed torque controller.<<ETX>>\",\"PeriodicalId\":287089,\"journal\":{\"name\":\"29th IEEE Conference on Decision and Control\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"29th IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1990.203395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"29th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1990.203395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A neural network-based controller for a two-link robot
A case of a multilayer perceptron (MLP) used for position control of a two-link robot is reported. Simulation results as well as the computational burden on neurocontrollers designed for robot control are presented. Such issues as the number of layers and number of nodes per layer are discussed. It is concluded that a neural network can be used to approximate a dynamical model of a robot. However, the error associated with this model is not nearly as good as that of conventional controllers, specifically a computed torque controller.<>
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
