An LMI-based decentralized H∞ filtering for interconnected linear systems

This paper focuses on decentralized H_∞ filtering problem for interconnected linear systems. The problem we address is to find a decentralized filter where each local filter is based only on local available information on its own subsystem and the overall filtering error is totally asymptotically stable and the L₂-gain from the exogenous noise input to the filtering error less than a prespecified level. This paper shows that the decentralized H_∞ filtering problem can be solved by using linear matrix inequality (LMI) techniques, which are numerically efficient due to recent advances in convex optimization.