{"title":"偏置扰动下离散最小相位对象的自适应最优鲁棒跟踪","authors":"V. Sokolov","doi":"10.1109/STAB49150.2020.9140470","DOIUrl":null,"url":null,"abstract":"This paper addresses a problem of adaptive optimal robust tracking of discrete-time minimum-phase SISO plant under biased total disturbance in the form of output uncertainty and bounded external disturbance. Coefficients of nominal model, a gain of output uncertainty, an upper bound of external disturbance, and bias are unknown to controller designer. The control criterion in the form of the worst-case steady-state tracking error over permitted uncertainties and disturbances is used as an identification criterion. Solution of the problem is based on polyhedral estimation of data-consistent parameters and computation of optimal current estimates.","PeriodicalId":166223,"journal":{"name":"2020 15th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference) (STAB)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive optimal robust tracking of discrete-time minimum-phase plant under biased disturbance\",\"authors\":\"V. Sokolov\",\"doi\":\"10.1109/STAB49150.2020.9140470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses a problem of adaptive optimal robust tracking of discrete-time minimum-phase SISO plant under biased total disturbance in the form of output uncertainty and bounded external disturbance. Coefficients of nominal model, a gain of output uncertainty, an upper bound of external disturbance, and bias are unknown to controller designer. The control criterion in the form of the worst-case steady-state tracking error over permitted uncertainties and disturbances is used as an identification criterion. Solution of the problem is based on polyhedral estimation of data-consistent parameters and computation of optimal current estimates.\",\"PeriodicalId\":166223,\"journal\":{\"name\":\"2020 15th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference) (STAB)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 15th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference) (STAB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STAB49150.2020.9140470\",\"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 15th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference) (STAB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STAB49150.2020.9140470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive optimal robust tracking of discrete-time minimum-phase plant under biased disturbance
This paper addresses a problem of adaptive optimal robust tracking of discrete-time minimum-phase SISO plant under biased total disturbance in the form of output uncertainty and bounded external disturbance. Coefficients of nominal model, a gain of output uncertainty, an upper bound of external disturbance, and bias are unknown to controller designer. The control criterion in the form of the worst-case steady-state tracking error over permitted uncertainties and disturbances is used as an identification criterion. Solution of the problem is based on polyhedral estimation of data-consistent parameters and computation of optimal current estimates.