{"title":"非线性系统的无模型预测控制","authors":"Qiubin Luo, Z. Han, Hong Zhu","doi":"10.1109/CCDC.2009.5195082","DOIUrl":null,"url":null,"abstract":"A model free predictive control is persented. This method does not need modeling in the predictive control. The eigenvector of generally model is identified and predicted by multi-layer recursive method. The model free predictive control law has advantage as well as model free control.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Model free predictive control of nonlinear system\",\"authors\":\"Qiubin Luo, Z. Han, Hong Zhu\",\"doi\":\"10.1109/CCDC.2009.5195082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A model free predictive control is persented. This method does not need modeling in the predictive control. The eigenvector of generally model is identified and predicted by multi-layer recursive method. The model free predictive control law has advantage as well as model free control.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5195082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5195082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A model free predictive control is persented. This method does not need modeling in the predictive control. The eigenvector of generally model is identified and predicted by multi-layer recursive method. The model free predictive control law has advantage as well as model free control.