{"title":"Parallel design of suboptimal regulators for singularly perturbed systems with multiple-time scales","authors":"Y. Wang, P. Frank","doi":"10.1109/CDC.1991.261315","DOIUrl":null,"url":null,"abstract":"The problem for near optimal control of linear systems with multiple-time-scale singular perturbations is studied by a descriptor variable approach. The near optimum regulator problem with multiple-time-scale singular perturbations is decomposed into a number of N+1 subregulator problems. The solutions are mutually independent, and are standard solutions of Riccati equations without parasitic parameters. The algorithm for parallel solutions of these subregulator problems is presented. A hierarchical combination of these suboptimal regulators leads to the near-optimal feedback controller. The spectral factorization of the linear quadratic regulator (LQR) shows that for small and unknown singularly perturbed parameters, the near-optimal controller will preserve the robustness gain and phase margin as established in the optimal LQR.<<ETX>>","PeriodicalId":344553,"journal":{"name":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","volume":" 666","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1991.261315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The problem for near optimal control of linear systems with multiple-time-scale singular perturbations is studied by a descriptor variable approach. The near optimum regulator problem with multiple-time-scale singular perturbations is decomposed into a number of N+1 subregulator problems. The solutions are mutually independent, and are standard solutions of Riccati equations without parasitic parameters. The algorithm for parallel solutions of these subregulator problems is presented. A hierarchical combination of these suboptimal regulators leads to the near-optimal feedback controller. The spectral factorization of the linear quadratic regulator (LQR) shows that for small and unknown singularly perturbed parameters, the near-optimal controller will preserve the robustness gain and phase margin as established in the optimal LQR.<>