{"title":"基于局部建模方法的分布式参数系统模型预测控制","authors":"Mengling Wang, Yang Zhang, H. Shi","doi":"10.1109/WCICA.2012.6358079","DOIUrl":null,"url":null,"abstract":"In this paper, a model-based predictive control strategy based on local modeling approach is proposed for distributed parameter system. As the partial differential equation (PDE) descriptions of the systems are unknown, the local modeling approach is used to estimate the dynamics of the system based on the input-output data. Based on finite local models, each local controller output can obtain through minimizing the local optimization objective. The global controlled outputs can be solved by linear programming where the deviations of the global spatial temporal outputs from their spatial set points over the prediction horizon are considered as the optimal objective. The accuracy and efficiency of the proposed methodologies are tested in the cross-flow heat exchanger.","PeriodicalId":114901,"journal":{"name":"Proceedings of the 10th World Congress on Intelligent Control and Automation","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model-based predictive control for distributed parameter systems based on local modeling approach\",\"authors\":\"Mengling Wang, Yang Zhang, H. Shi\",\"doi\":\"10.1109/WCICA.2012.6358079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a model-based predictive control strategy based on local modeling approach is proposed for distributed parameter system. As the partial differential equation (PDE) descriptions of the systems are unknown, the local modeling approach is used to estimate the dynamics of the system based on the input-output data. Based on finite local models, each local controller output can obtain through minimizing the local optimization objective. The global controlled outputs can be solved by linear programming where the deviations of the global spatial temporal outputs from their spatial set points over the prediction horizon are considered as the optimal objective. The accuracy and efficiency of the proposed methodologies are tested in the cross-flow heat exchanger.\",\"PeriodicalId\":114901,\"journal\":{\"name\":\"Proceedings of the 10th World Congress on Intelligent Control and Automation\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2012.6358079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2012.6358079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model-based predictive control for distributed parameter systems based on local modeling approach
In this paper, a model-based predictive control strategy based on local modeling approach is proposed for distributed parameter system. As the partial differential equation (PDE) descriptions of the systems are unknown, the local modeling approach is used to estimate the dynamics of the system based on the input-output data. Based on finite local models, each local controller output can obtain through minimizing the local optimization objective. The global controlled outputs can be solved by linear programming where the deviations of the global spatial temporal outputs from their spatial set points over the prediction horizon are considered as the optimal objective. The accuracy and efficiency of the proposed methodologies are tested in the cross-flow heat exchanger.