{"title":"基于模型的时滞网络控制系统预测控制","authors":"Koji Kobayashi, Hiromu Noritsuki, Y. Uchimura","doi":"10.1109/IECON.2017.8216976","DOIUrl":null,"url":null,"abstract":"This paper proposes a control method that compensates for a system with time delay by predicting the future states of the plant. The proposed method contains a state predictor that predicts the future values of a system. Furthermore, the proposed method also considers the uncertainty of the model in terms of the modeling error, which might cause the predicted value to degrade the performance of the system or even destabilize it in the worst case. The disturbance in the remote plant is explicitly considered and is compensated for by locating a feedback controller in the remote side. This paper described the proposed control method based on model-based predictive control that considers modeling error. The stability of the proposed system is analyzed, and performance of the method is evaluated in comparison with conventional methods using numerical simulation results.","PeriodicalId":13098,"journal":{"name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","volume":"59 1","pages":"5633-5638"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Model based predictive control for networked control system with time delay\",\"authors\":\"Koji Kobayashi, Hiromu Noritsuki, Y. Uchimura\",\"doi\":\"10.1109/IECON.2017.8216976\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a control method that compensates for a system with time delay by predicting the future states of the plant. The proposed method contains a state predictor that predicts the future values of a system. Furthermore, the proposed method also considers the uncertainty of the model in terms of the modeling error, which might cause the predicted value to degrade the performance of the system or even destabilize it in the worst case. The disturbance in the remote plant is explicitly considered and is compensated for by locating a feedback controller in the remote side. This paper described the proposed control method based on model-based predictive control that considers modeling error. The stability of the proposed system is analyzed, and performance of the method is evaluated in comparison with conventional methods using numerical simulation results.\",\"PeriodicalId\":13098,\"journal\":{\"name\":\"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society\",\"volume\":\"59 1\",\"pages\":\"5633-5638\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECON.2017.8216976\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2017.8216976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model based predictive control for networked control system with time delay
This paper proposes a control method that compensates for a system with time delay by predicting the future states of the plant. The proposed method contains a state predictor that predicts the future values of a system. Furthermore, the proposed method also considers the uncertainty of the model in terms of the modeling error, which might cause the predicted value to degrade the performance of the system or even destabilize it in the worst case. The disturbance in the remote plant is explicitly considered and is compensated for by locating a feedback controller in the remote side. This paper described the proposed control method based on model-based predictive control that considers modeling error. The stability of the proposed system is analyzed, and performance of the method is evaluated in comparison with conventional methods using numerical simulation results.