{"title":"永磁单级电磁选针器多目标优化设计","authors":"Tao Wang, Zhen Mao, Cheng Ju","doi":"10.1117/12.2672266","DOIUrl":null,"url":null,"abstract":"A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"4571 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective optimization design of single-stage electromagnetic needle selector with permanent magnet\",\"authors\":\"Tao Wang, Zhen Mao, Cheng Ju\",\"doi\":\"10.1117/12.2672266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.\",\"PeriodicalId\":290902,\"journal\":{\"name\":\"International Conference on Mechatronics Engineering and Artificial Intelligence\",\"volume\":\"4571 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Mechatronics Engineering and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2672266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Mechatronics Engineering and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2672266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective optimization design of single-stage electromagnetic needle selector with permanent magnet
A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
