Gain-Scheduled H2 Filter Synthesis via Polynomially Parameter-Dependent Lyapunov Functions with Inexact Scheduling Parameters
نویسنده
چکیده
This paper addresses the design problem of GainScheduled (GS) H2 filters for Linear Parameter-Varying (LPV) systems under the condition that only inexactly measured scheduling parameters are available. The state-space matrices of the LPV systems are supposed to be polynomially parameter dependent and those of filters which are to be designed are supposed to be rationally parameter dependent. The uncertainties in the measured scheduling parameters are supposed to lie in a priori defined convex set. Using structured polynomially Parameter-Dependent Lyapunov Functions (PDLFs), we give a design method of GS H2 filters, which are robust against the uncertainties in the measured scheduling parameters, in terms of parametrically affine Linear Matrix Inequalities (LMIs). Our proposed method includes robust filter design as a special case. A numerical example demonstrates the effectiveness of our method.
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