{"title":"数据驱动-基于Lyapunov方法的自适应单神经元预测控制器","authors":"L. Jia, Luming Cao, M. Chiu","doi":"10.1109/WCICA.2011.5970724","DOIUrl":null,"url":null,"abstract":"In this paper, a novel data driven-adaptive single neuron predictive controller is proposed. The self-tuning algorithm for the single neuron predictive controller is derived by a rigorous analysis based on the Lyapunov method such that the predicted tracking error convergences asymptotically. Simulation results are presented to illustrate the proposed adaptive predictive controller and a comparison with its conventional counterparts is made.","PeriodicalId":211049,"journal":{"name":"2011 9th World Congress on Intelligent Control and Automation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data driven- Adaptive single neuron predictive controller based on Lyapunov approach\",\"authors\":\"L. Jia, Luming Cao, M. Chiu\",\"doi\":\"10.1109/WCICA.2011.5970724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a novel data driven-adaptive single neuron predictive controller is proposed. The self-tuning algorithm for the single neuron predictive controller is derived by a rigorous analysis based on the Lyapunov method such that the predicted tracking error convergences asymptotically. Simulation results are presented to illustrate the proposed adaptive predictive controller and a comparison with its conventional counterparts is made.\",\"PeriodicalId\":211049,\"journal\":{\"name\":\"2011 9th World Congress on Intelligent Control and Automation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 9th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2011.5970724\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2011.5970724","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data driven- Adaptive single neuron predictive controller based on Lyapunov approach
In this paper, a novel data driven-adaptive single neuron predictive controller is proposed. The self-tuning algorithm for the single neuron predictive controller is derived by a rigorous analysis based on the Lyapunov method such that the predicted tracking error convergences asymptotically. Simulation results are presented to illustrate the proposed adaptive predictive controller and a comparison with its conventional counterparts is made.