{"title":"保标称稳定非线性模型预测控制的若干性质","authors":"Shuyou Yu, Ting Qu, Hong Chen","doi":"10.1109/MIC.2013.6758209","DOIUrl":null,"url":null,"abstract":"In this note, we discuss the properties of model predictive control of nonlinear systems with input constraints. It shows that the prediction trajectory will not leave the terminal set once it enters into it, and the terminal state lies in a sublevel set of the terminal set if there exists a point of the prediction trajectory lying in the sublevel set. Furthermore, we show that the feasible set of the related optimization problem is a bounded set around the origin.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Some properties of nonlinear model predictive control with guaranteed nominal stability\",\"authors\":\"Shuyou Yu, Ting Qu, Hong Chen\",\"doi\":\"10.1109/MIC.2013.6758209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this note, we discuss the properties of model predictive control of nonlinear systems with input constraints. It shows that the prediction trajectory will not leave the terminal set once it enters into it, and the terminal state lies in a sublevel set of the terminal set if there exists a point of the prediction trajectory lying in the sublevel set. Furthermore, we show that the feasible set of the related optimization problem is a bounded set around the origin.\",\"PeriodicalId\":404630,\"journal\":{\"name\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIC.2013.6758209\",\"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 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6758209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Some properties of nonlinear model predictive control with guaranteed nominal stability
In this note, we discuss the properties of model predictive control of nonlinear systems with input constraints. It shows that the prediction trajectory will not leave the terminal set once it enters into it, and the terminal state lies in a sublevel set of the terminal set if there exists a point of the prediction trajectory lying in the sublevel set. Furthermore, we show that the feasible set of the related optimization problem is a bounded set around the origin.