{"title":"基于矩阵不等式的考虑模型不确定性和外部干扰的车辆鲁棒模型预测控制*","authors":"Wenjun Liu, Guang Chen, Alois Knoll","doi":"10.1109/CVCI51460.2020.9338626","DOIUrl":null,"url":null,"abstract":"Model uncertainties and external disturbances can inevitably affect vehicle dynamic control accuracy and even cause the vehicle system to be unstable and unsafe. Therefore, vehicle dynamic controller must be able to suppress the influence of model uncertainties and external disturbances on vehicle dynamic control performance. To this aim, we design a matrix inequalities (both bilinear matrix inequalities (BMIs) and linear matrix inequalities (LMIs) are involved) based robust model predictive controller for vehicle dynamic control. Robust positive invariant (RPI) set is used to guarantee the controller is robust and to construct the matrix inequality equations. We test the usefulness of the proposed controller via a numerical example.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties and External Disturbances*\",\"authors\":\"Wenjun Liu, Guang Chen, Alois Knoll\",\"doi\":\"10.1109/CVCI51460.2020.9338626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Model uncertainties and external disturbances can inevitably affect vehicle dynamic control accuracy and even cause the vehicle system to be unstable and unsafe. Therefore, vehicle dynamic controller must be able to suppress the influence of model uncertainties and external disturbances on vehicle dynamic control performance. To this aim, we design a matrix inequalities (both bilinear matrix inequalities (BMIs) and linear matrix inequalities (LMIs) are involved) based robust model predictive controller for vehicle dynamic control. Robust positive invariant (RPI) set is used to guarantee the controller is robust and to construct the matrix inequality equations. We test the usefulness of the proposed controller via a numerical example.\",\"PeriodicalId\":119721,\"journal\":{\"name\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVCI51460.2020.9338626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties and External Disturbances*
Model uncertainties and external disturbances can inevitably affect vehicle dynamic control accuracy and even cause the vehicle system to be unstable and unsafe. Therefore, vehicle dynamic controller must be able to suppress the influence of model uncertainties and external disturbances on vehicle dynamic control performance. To this aim, we design a matrix inequalities (both bilinear matrix inequalities (BMIs) and linear matrix inequalities (LMIs) are involved) based robust model predictive controller for vehicle dynamic control. Robust positive invariant (RPI) set is used to guarantee the controller is robust and to construct the matrix inequality equations. We test the usefulness of the proposed controller via a numerical example.