{"title":"大时滞过程中灰色预测模型改进的控制研究","authors":"L. Junfeng, Xia Junjian, Hu Baoan, Zhang Xinwei","doi":"10.1109/CCDC.2012.6244139","DOIUrl":null,"url":null,"abstract":"Based on ideals of improving on forecasting of the grey model, an improved grey forecasting algorithm was given. The model was built by using data accumulation with weighted method, and the model is improved by changing the initiate condition. The coefficient of the GM(1,1) model is applied to determine the prediction steps. By combining GM(1,1) model with PID, the grey predicting control system for controlling the large time delay process is proposed. The results of simulation show that, comparing with traditional PID control method, the proposed algorithm has better flexibility and robustness, and also can fairly improve the control performances.","PeriodicalId":345790,"journal":{"name":"2012 24th Chinese Control and Decision Conference (CCDC)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Control study of improvement on grey predictive model in large time delay process\",\"authors\":\"L. Junfeng, Xia Junjian, Hu Baoan, Zhang Xinwei\",\"doi\":\"10.1109/CCDC.2012.6244139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on ideals of improving on forecasting of the grey model, an improved grey forecasting algorithm was given. The model was built by using data accumulation with weighted method, and the model is improved by changing the initiate condition. The coefficient of the GM(1,1) model is applied to determine the prediction steps. By combining GM(1,1) model with PID, the grey predicting control system for controlling the large time delay process is proposed. The results of simulation show that, comparing with traditional PID control method, the proposed algorithm has better flexibility and robustness, and also can fairly improve the control performances.\",\"PeriodicalId\":345790,\"journal\":{\"name\":\"2012 24th Chinese Control and Decision Conference (CCDC)\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 24th Chinese Control and Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2012.6244139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 24th Chinese Control and Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2012.6244139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Control study of improvement on grey predictive model in large time delay process
Based on ideals of improving on forecasting of the grey model, an improved grey forecasting algorithm was given. The model was built by using data accumulation with weighted method, and the model is improved by changing the initiate condition. The coefficient of the GM(1,1) model is applied to determine the prediction steps. By combining GM(1,1) model with PID, the grey predicting control system for controlling the large time delay process is proposed. The results of simulation show that, comparing with traditional PID control method, the proposed algorithm has better flexibility and robustness, and also can fairly improve the control performances.