{"title":"一种自适应进化策略及其在大飞行包线下飞机控制律优化中的应用","authors":"Guangwen Li, Qiuling Jia, Jingping Shi","doi":"10.1109/AICI.2009.218","DOIUrl":null,"url":null,"abstract":"The searching precision and the global searching ability of Evolutionary Strategy (ES) depend on the selection of the mutation step. In order to enhance the global searching ability and precision, an adaptive evolutionary strategy based on the feedback and sharing mechanism (ESBFSM) is proposed, in which the information of the current optimal searching result and sharing degree is fed into the mutating formula. By tuning the variance of the mutation operator according to the feedback information, the mutation step of ES is changed with the current searching result. And a part of individuals of the population in the later searching procedure keep higher probability of jumping out of the local minimum by the sharing mechanism. To validate the optimizing effect of the ESBFSM, the optimization of an transport aircraf’s control law in the large flight envelope is done by this method, the result shows the ESBFSM is effective in optimization of the complex control system","PeriodicalId":289808,"journal":{"name":"2009 International Conference on Artificial Intelligence and Computational Intelligence","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Adaptive Evolutionary Strategy and its Application in the Optimization of the Aircraft Control Law in the Large Flight Envelope\",\"authors\":\"Guangwen Li, Qiuling Jia, Jingping Shi\",\"doi\":\"10.1109/AICI.2009.218\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The searching precision and the global searching ability of Evolutionary Strategy (ES) depend on the selection of the mutation step. In order to enhance the global searching ability and precision, an adaptive evolutionary strategy based on the feedback and sharing mechanism (ESBFSM) is proposed, in which the information of the current optimal searching result and sharing degree is fed into the mutating formula. By tuning the variance of the mutation operator according to the feedback information, the mutation step of ES is changed with the current searching result. And a part of individuals of the population in the later searching procedure keep higher probability of jumping out of the local minimum by the sharing mechanism. To validate the optimizing effect of the ESBFSM, the optimization of an transport aircraf’s control law in the large flight envelope is done by this method, the result shows the ESBFSM is effective in optimization of the complex control system\",\"PeriodicalId\":289808,\"journal\":{\"name\":\"2009 International Conference on Artificial Intelligence and Computational Intelligence\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Artificial Intelligence and Computational Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICI.2009.218\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Artificial Intelligence and Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICI.2009.218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Adaptive Evolutionary Strategy and its Application in the Optimization of the Aircraft Control Law in the Large Flight Envelope
The searching precision and the global searching ability of Evolutionary Strategy (ES) depend on the selection of the mutation step. In order to enhance the global searching ability and precision, an adaptive evolutionary strategy based on the feedback and sharing mechanism (ESBFSM) is proposed, in which the information of the current optimal searching result and sharing degree is fed into the mutating formula. By tuning the variance of the mutation operator according to the feedback information, the mutation step of ES is changed with the current searching result. And a part of individuals of the population in the later searching procedure keep higher probability of jumping out of the local minimum by the sharing mechanism. To validate the optimizing effect of the ESBFSM, the optimization of an transport aircraf’s control law in the large flight envelope is done by this method, the result shows the ESBFSM is effective in optimization of the complex control system