{"title":"不变集框架下约束广义预测控制的可行性","authors":"Sorin Olaru, D. Dumur","doi":"10.1080/1448837X.2005.11464116","DOIUrl":null,"url":null,"abstract":"Feasibility issues of generalized predictive control structures are analysed in case of constraints on the input, output or other auxiliary variables with linear dependence on the system variables. The constraints are formulated as sets of linear equality or inequality relations on the input variables that would represent the optimisation domain for a quadratic cost function. Looking as the main goal at the prediction of the feasibility of this optimisation problem, sufficient conditions are presented in this direction. The main contribution is the description of the optimisation domain as an invariant set with respect to the predictive control law dynamics. The main advantage is that all the results are based on off-line calculations offering qualitative information prior to the effective implementation.","PeriodicalId":169932,"journal":{"name":"2004 5th Asian Control Conference (IEEE Cat. No.04EX904)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Feasibility of constrained generalized predictive control within invariant sets framework\",\"authors\":\"Sorin Olaru, D. Dumur\",\"doi\":\"10.1080/1448837X.2005.11464116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Feasibility issues of generalized predictive control structures are analysed in case of constraints on the input, output or other auxiliary variables with linear dependence on the system variables. The constraints are formulated as sets of linear equality or inequality relations on the input variables that would represent the optimisation domain for a quadratic cost function. Looking as the main goal at the prediction of the feasibility of this optimisation problem, sufficient conditions are presented in this direction. The main contribution is the description of the optimisation domain as an invariant set with respect to the predictive control law dynamics. The main advantage is that all the results are based on off-line calculations offering qualitative information prior to the effective implementation.\",\"PeriodicalId\":169932,\"journal\":{\"name\":\"2004 5th Asian Control Conference (IEEE Cat. No.04EX904)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 5th Asian Control Conference (IEEE Cat. No.04EX904)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/1448837X.2005.11464116\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 5th Asian Control Conference (IEEE Cat. No.04EX904)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1448837X.2005.11464116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feasibility of constrained generalized predictive control within invariant sets framework
Feasibility issues of generalized predictive control structures are analysed in case of constraints on the input, output or other auxiliary variables with linear dependence on the system variables. The constraints are formulated as sets of linear equality or inequality relations on the input variables that would represent the optimisation domain for a quadratic cost function. Looking as the main goal at the prediction of the feasibility of this optimisation problem, sufficient conditions are presented in this direction. The main contribution is the description of the optimisation domain as an invariant set with respect to the predictive control law dynamics. The main advantage is that all the results are based on off-line calculations offering qualitative information prior to the effective implementation.