{"title":"基于智能体的感应电机驱动控制方法","authors":"C. Caileanu","doi":"10.1109/INES.1997.632443","DOIUrl":null,"url":null,"abstract":"An agent based approach to induction motor control is proposed in this paper. After a short introduction in intelligent agents (controllers) special attention is given to the learning element. Two main learning paradigms, supervised learning and reinforcement learning are used for the drive to exhibit rational behavior. Artificial neural networks are used to learn different mappings inside the intelligent current controller. Matlab(R) has been used as the simulation environment.","PeriodicalId":161975,"journal":{"name":"Proceedings of IEEE International Conference on Intelligent Engineering Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An agent-based approach to induction motor drives control\",\"authors\":\"C. Caileanu\",\"doi\":\"10.1109/INES.1997.632443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An agent based approach to induction motor control is proposed in this paper. After a short introduction in intelligent agents (controllers) special attention is given to the learning element. Two main learning paradigms, supervised learning and reinforcement learning are used for the drive to exhibit rational behavior. Artificial neural networks are used to learn different mappings inside the intelligent current controller. Matlab(R) has been used as the simulation environment.\",\"PeriodicalId\":161975,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.1997.632443\",\"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 IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.1997.632443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An agent-based approach to induction motor drives control
An agent based approach to induction motor control is proposed in this paper. After a short introduction in intelligent agents (controllers) special attention is given to the learning element. Two main learning paradigms, supervised learning and reinforcement learning are used for the drive to exhibit rational behavior. Artificial neural networks are used to learn different mappings inside the intelligent current controller. Matlab(R) has been used as the simulation environment.