Sensor Networks With Random Link Failures: Distributed Filtering for T–S Fuzzy Systems

TLDR: Sufficient conditions for the obtained filtering error dynamic system are proposed by applying an comparison model and the scaled small gain theorem and the solution of the parameters of the distributed fuzzy filters is characterized in terms of the feasibility of a convex optimization problem.

Abstract: The paper is concerned with the problem of distributed fuzzy filter design for a class of sensor networks described by discrete-time T-S fuzzy systems with time-varying delays and multiple probabilistic packet losses. In sensor network, each individual sensor can receive not only its own measurement but also its neighboring sensors' measurements according to the interconnection topology to estimate the system states. Our attention is focused on the design of distributed fuzzy filters to guarantee the filtering error dynamic system to be mean-square asymptotically stable with an average \mathscr H∞ performance. Sufficient conditions for the obtained filtering error dynamic system are proposed by applying an comparison model and the scaled small gain theorem. Based on the measurements and estimates of the system states and its neighbors for each sensor, the solution of the parameters of the distributed fuzzy filters is characterized in terms of the feasibility of a convex optimization problem. Finally, an illustrative example is provided to illustrate the effectiveness of the proposed approaches in sensor networks.