{"title":"MCFC系统运行优化的PID自整定策略","authors":"Y. Cheon, Donghyun Lee, In-Beum Lee, S. Sung","doi":"10.1109/ASCC.2013.6606304","DOIUrl":null,"url":null,"abstract":"This paper presents a new strategy of PID autotuning which is combined with an operational optimization for Molten Carbonate Fuel Cell (MCFC) systems to track the power demand with high efficiency. The PID auto-tuning methodology is based on frequency response identification and a model reduction to a fractional low order model. And the operational optimization problem is formulated by a radial basis functional neural network model. The proposed control strategy provides good control performance for the successive power demand changes and successfully compensates the nonlinearity of the MCFC system.","PeriodicalId":6304,"journal":{"name":"2013 9th Asian Control Conference (ASCC)","volume":"10 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A new PID auto-tuning strategy with operational optimization for MCFC systems\",\"authors\":\"Y. Cheon, Donghyun Lee, In-Beum Lee, S. Sung\",\"doi\":\"10.1109/ASCC.2013.6606304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new strategy of PID autotuning which is combined with an operational optimization for Molten Carbonate Fuel Cell (MCFC) systems to track the power demand with high efficiency. The PID auto-tuning methodology is based on frequency response identification and a model reduction to a fractional low order model. And the operational optimization problem is formulated by a radial basis functional neural network model. The proposed control strategy provides good control performance for the successive power demand changes and successfully compensates the nonlinearity of the MCFC system.\",\"PeriodicalId\":6304,\"journal\":{\"name\":\"2013 9th Asian Control Conference (ASCC)\",\"volume\":\"10 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th Asian Control Conference (ASCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASCC.2013.6606304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th Asian Control Conference (ASCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASCC.2013.6606304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new PID auto-tuning strategy with operational optimization for MCFC systems
This paper presents a new strategy of PID autotuning which is combined with an operational optimization for Molten Carbonate Fuel Cell (MCFC) systems to track the power demand with high efficiency. The PID auto-tuning methodology is based on frequency response identification and a model reduction to a fractional low order model. And the operational optimization problem is formulated by a radial basis functional neural network model. The proposed control strategy provides good control performance for the successive power demand changes and successfully compensates the nonlinearity of the MCFC system.