{"title":"基于进化算法的预测-关于控制变量领域的实现方面","authors":"V. Mînzu, Iulian Arama, C. Vlad","doi":"10.1109/ICSTCC55426.2022.9931827","DOIUrl":null,"url":null,"abstract":"This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Receding Horizon Control structures whose Controller can integrate an EA to generate the optimal predictions. In a previous paper, the authors proposed the control range adaptation to diminish the computational complexity. An additional technique called control range tuning is proposed in this paper.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictions based on Evolutionary Algorithms – Implementation Aspects regarding the Control Variables' Domain\",\"authors\":\"V. Mînzu, Iulian Arama, C. Vlad\",\"doi\":\"10.1109/ICSTCC55426.2022.9931827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Receding Horizon Control structures whose Controller can integrate an EA to generate the optimal predictions. In a previous paper, the authors proposed the control range adaptation to diminish the computational complexity. An additional technique called control range tuning is proposed in this paper.\",\"PeriodicalId\":220845,\"journal\":{\"name\":\"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSTCC55426.2022.9931827\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTCC55426.2022.9931827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictions based on Evolutionary Algorithms – Implementation Aspects regarding the Control Variables' Domain
This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Receding Horizon Control structures whose Controller can integrate an EA to generate the optimal predictions. In a previous paper, the authors proposed the control range adaptation to diminish the computational complexity. An additional technique called control range tuning is proposed in this paper.