Robust H∞ Filtering for Continuous Time-Varying Uncertain Systems with Adaptive Mechanism

This paper studies the problem of designing robust H∞ filters for linear uncertain systems. The uncertainty parameters are assumed to be time-varying, unknown, but bounded, which appear affinely in the matrices of system models. An adaptive mechanism is introduced to construct novel filters with variable gains, which can reduce the conservativeness of traditional robust H∞ filters. The proposed adaptive filter design conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the asymptotically stability and optimize H∞ performances of the resulting closed-loop systems. A numerical example is presented to illustrate the effectiveness of the proposed strategy.