{"title":"Further Results of Robust Observer-Based Control Synthesis for Saturated Linear Parameter Varying Systems","authors":"V. L. B. Tuan, A. Hajjaji, O. Pagès","doi":"10.1109/anzcc53563.2021.9628278","DOIUrl":null,"url":null,"abstract":"This paper deals with the observer-based robust control design problem for affine quadratic systems with parametric uncertainties. The prerequisite design conditions derive via the Lyapunov function with saturation constraints enforced by sector nonlinearity conditions. The non-convex and bilinear problems involved in the stabilization condition are converted into convex optimization problems using Young’s inequality, and the cone-complementary linearization. Then, controller and observer gains are obtained by set feasible solutions of linear matrix inequality (LMI) conditions under ${\\mathcal{L}_2}$-bounded disturbance. The effectiveness of the proposed design methodology is demonstrated through numerical simulations.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"29 5-6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Australian & New Zealand Control Conference (ANZCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/anzcc53563.2021.9628278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper deals with the observer-based robust control design problem for affine quadratic systems with parametric uncertainties. The prerequisite design conditions derive via the Lyapunov function with saturation constraints enforced by sector nonlinearity conditions. The non-convex and bilinear problems involved in the stabilization condition are converted into convex optimization problems using Young’s inequality, and the cone-complementary linearization. Then, controller and observer gains are obtained by set feasible solutions of linear matrix inequality (LMI) conditions under ${\mathcal{L}_2}$-bounded disturbance. The effectiveness of the proposed design methodology is demonstrated through numerical simulations.