Mahmoud M.S.Boujarwah A.S.MSA UniversityDokkiEgypt; Department of Computer EngineeringKuwait UniversitySafat-13060Kuwait2020-01-252020-01-25200110577122https://doi.org/10.1109/81.948442https://cutt.ly/SrK6423ScopusIn this paper, we investigate the problem of H? filtering for a class of linear parameter-varying (LPV) systems in which the state-space matrices depend affinely on time-varying parameters. We employ the notion of affine quadratic stability using parameter-dependent Lyapunov functionals. We develop a linear parameter-dependent filter such that the estimation erorr is affinely quadratically stable with a prescribed performance measure. It is established that the solvability conditions can be expressed by linear matrix inequalities which are then evaluated at the extreme points of the admissible parameter set. Simulation results of a typical example are presented.EnglishLinear parameter-varying systemsQuadratic stabilityRobust H? filteringComputer simulationControl system synthesisLyapunov methodsOptimal control systemsOptimizationParameter estimationRobustness (control systems)State space methodsSystem stabilityTime varying control systemsLinear matrix inequalitiesLinear parameter-varying systemQuadratic stabilityLinear control systemsArticlehttps://doi.org/10.1109/81.948442