Optimal filtering with random sensor delay, multiple packet dropout and uncertain observations

Abstract

This paper studies the problem of optimal filtering of discrete-time systems with random sensor delay, multiple packet dropout and uncertain observation. The random sensor delay, multiple packet dropout or uncertainty in observation is transformed to a stochastic parameter in the system representation. A new formulation enables us to design an optimal filter for a system with multiple packet dropout in sensor data. Based on a stochastic definition of the -norm of a system with a stochastic parameter, new relations for stochastic -norm are derived. The stochastic -norm of the estimation error is used as a criterion for the filter design. The relations derived for the new norm definition are used to obtain a set of linear matrix inequalities (LMIs) to solve the filter design problems. Simulation examples show the effectiveness of the proposed method.

Acknowledgements

This research was partially supported by NSERC. The authors acknowledge and really appreciate the anonymous reviewers for their careful reading and helpful comments and suggestions.