A New Approach for Robust and Reduced Order H/spl infin/ Filtering

The objective of this paper is to develop a practical methodology for designing full and reduced order H_infin filter for plants with polytopic model uncertainty. Polytopic models provide a very general framework for describing uncertainties in engineering applications. Because the polytopic model description is convex, it is amenable for a linear matrix inequality (LMI) formulation. Reduced order filters are desirable in applications where fast data processing is necessary. To improve robustness to model uncertainties, this paper reformulates an H₂ filter design technique as a reduced order H_infin filter design methodology. Lyapunov functions are replaced with parameter-dependent Lyapunov functions to provide less conservative results. As the problem is formulated as an LMI, an admissible filter with suitable dynamic behavior can be obtained from the solution of a convex optimization problem. The advantages of this approach over earlier approaches are highlighted in a simple computational example