{"title":"四旋翼无人机的级联模型预测控制","authors":"X. Chen, Liuping Wang","doi":"10.1109/AUCC.2013.6697298","DOIUrl":null,"url":null,"abstract":"When using a linear controller for controlling a non-linear system, the controller is most effective when the system is working near the operating conditions. This paper proposes a model predictive controller with cascaded structure, which has the ability to maintain the state variables within the vicinity of a given operating condition by imposing operational constraints. The controller is validated on the quadrotor position control problem and shows satisfactory performance.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Cascaded model predictive control of a quadrotor UAV\",\"authors\":\"X. Chen, Liuping Wang\",\"doi\":\"10.1109/AUCC.2013.6697298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When using a linear controller for controlling a non-linear system, the controller is most effective when the system is working near the operating conditions. This paper proposes a model predictive controller with cascaded structure, which has the ability to maintain the state variables within the vicinity of a given operating condition by imposing operational constraints. The controller is validated on the quadrotor position control problem and shows satisfactory performance.\",\"PeriodicalId\":177490,\"journal\":{\"name\":\"2013 Australian Control Conference\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Australian Control Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUCC.2013.6697298\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Australian Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUCC.2013.6697298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cascaded model predictive control of a quadrotor UAV
When using a linear controller for controlling a non-linear system, the controller is most effective when the system is working near the operating conditions. This paper proposes a model predictive controller with cascaded structure, which has the ability to maintain the state variables within the vicinity of a given operating condition by imposing operational constraints. The controller is validated on the quadrotor position control problem and shows satisfactory performance.