Reliable H∞ filter design for sampled-data systems with consideration of probabilistic sensor signal distortion

This study is concerned with the reliable filtering problem for the sampled-data system subject to a class of probabilistic sensor signals distortion. A new distortion model is developed by introducing a diagonal random matrix whose elements obey the Gaussian distribution. The main purpose in this study is to design a filter such that the error dynamics of the filtering process subject to the probabilistic sensor signal distortion is mean-square asymptotically stable. Based on the modified delay-central-point (DCP) method and the convexity property of the matrix inequality, new criteria are derived for the existence of the desired H∞ filters, by which it leads to much less conservative analysis results. Simulation results are provided to illustrate the effectiveness of the proposed method.