Robust Filtering for a Class of Linear Parameter-Varying Systems

In this paper, we investigate the problem of 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 error is affinely quadratically stable with a prescribed perfor- mance measure. It is established that the solvability conditions can be ex- pressed by linear matrix inequalities which are then evaluated at the ex- treme points of the admissible parameter set. Simulation results of a typical example are presented.

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