{"title":"DDEKF learning for fast nonlinear adaptive inverse control","authors":"G. Plett, H. Bottrich","doi":"10.1109/IJCNN.2002.1007464","DOIUrl":null,"url":null,"abstract":"Adaptive inverse control (AIC) uses three adaptive filters: plant model, controller and disturbance canceler. Methods are known for quick and efficient training of these filters if the plant is linear; however, known methods for nonlinear AIC learn very slowly. This paper modifies the standard nonlinear AIC learning methods (based on real-time recurrent learning) using the dynamic-decoupled-extended Kalman-filter (DDEKF). The training becomes significantly faster.","PeriodicalId":382771,"journal":{"name":"Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2002.1007464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Adaptive inverse control (AIC) uses three adaptive filters: plant model, controller and disturbance canceler. Methods are known for quick and efficient training of these filters if the plant is linear; however, known methods for nonlinear AIC learn very slowly. This paper modifies the standard nonlinear AIC learning methods (based on real-time recurrent learning) using the dynamic-decoupled-extended Kalman-filter (DDEKF). The training becomes significantly faster.
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