文章基本信息

标题：Multi-objective Unified qLPV Observer: Application to a Semi-active Suspension System
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作者：Gia Quoc Bao Tran ; Thanh-Phong Pham ; Olivier Sename 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：8
页码：136-141
DOI：10.1016/j.ifacol.2021.08.593
语种：English
出版社：Elsevier
摘要：AbstractThis work concerns the design of a multi-objective unified qLPV observer for the state estimation problem in LPV systems with a parameter-dependent control input matrix. The standard forms of the system and the observer are first presented, where the observer matrices are functions of the estimated states (qLPV problem). The effects of bounded unknown input disturbances are decoupled from the estimation error thanks to the parameterization of the observer matrices. To treat the disturbance caused by inexact scheduling parameters, we introduce an upper bound on the parameter estimation error, which is considered uncertainty. Then, the effects of the control input and the random measurement noise on the estimation error are minimized using the H∞and generalized H2conditions, respectively, as a multi-objective optimization problem. In the solution of the LMI sets, the projection lemma is applied to reduce the high conservativeness that would otherwise lead to suboptimal results. Then this observer is applied to a semi-active automotive suspension system written in LPV form, using simulations with real data measured from our experiment test platform, and compared with the linear time-invariant H∞and H2observers.
关键词：KeywordsUnified observerlinear parameter-varying systemsH∞generalized H2projection lemmasemi-active suspension