Robust ℋ℞ filtering for linear discrete-time state-space models with uncertain time-varying parameters

This paper deals with the design of robust ℋ
℞
filters for linear discrete-time state-space models with uncertain time-varying parameters. The admissible parameters values and rates of variation are assumed to belong to a polytope with known vertices. A method based on a parameter-dependent Lyapunov function is proposed for designing a linear stationary asymptotically stable filter that provides a prescribed ℋ
℞
performance irrespective of the uncertain parameters.