{"title":"风能转换系统的H∞最优滤波与控制","authors":"H. M. Nguyen, D. Naidu, S. Mousavinezhad","doi":"10.1109/EIT.2013.6632650","DOIUrl":null,"url":null,"abstract":"This paper presents a reduced-order H∞ optimal control for wind energy conversion systems. Two different timescale (slow and fast) dynamics of wind energy conversion systems are separated and processed independently using the singular perturbation theory. By using the decomposition technique, low-order, independent H∞ optimal filters and controllers are obtained, which provide computational advantages and enable implementations with different sampling rates. The control robustness and efficiency are shown by computer simulations.","PeriodicalId":201202,"journal":{"name":"IEEE International Conference on Electro-Information Technology , EIT 2013","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"H∞ optimal filtering and control of wind energy conversion systems\",\"authors\":\"H. M. Nguyen, D. Naidu, S. Mousavinezhad\",\"doi\":\"10.1109/EIT.2013.6632650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a reduced-order H∞ optimal control for wind energy conversion systems. Two different timescale (slow and fast) dynamics of wind energy conversion systems are separated and processed independently using the singular perturbation theory. By using the decomposition technique, low-order, independent H∞ optimal filters and controllers are obtained, which provide computational advantages and enable implementations with different sampling rates. The control robustness and efficiency are shown by computer simulations.\",\"PeriodicalId\":201202,\"journal\":{\"name\":\"IEEE International Conference on Electro-Information Technology , EIT 2013\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Electro-Information Technology , EIT 2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIT.2013.6632650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Electro-Information Technology , EIT 2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2013.6632650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
H∞ optimal filtering and control of wind energy conversion systems
This paper presents a reduced-order H∞ optimal control for wind energy conversion systems. Two different timescale (slow and fast) dynamics of wind energy conversion systems are separated and processed independently using the singular perturbation theory. By using the decomposition technique, low-order, independent H∞ optimal filters and controllers are obtained, which provide computational advantages and enable implementations with different sampling rates. The control robustness and efficiency are shown by computer simulations.