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Distributed robust filtering with \(H_\infty\) consensus of estimates. (English) Zbl 1209.93152
Summary: The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory. The main result is a sufficient condition which guarantees a suboptimal \(H_\infty\) level of disagreement of estimates in a network of filters. It involves solving a convex optimization/feasibility problem subject to Linear Matrix Inequality (LMI) constraints. The special case of balanced interconnection graphs is also considered. A gradient descent type algorithm is presented which allows the nodes to compute their estimator parameters in a decentralized manner. The proposed approach is applied to the problem of observer-based robust synchronization of a nonlinear network to an isolated node.

MSC:
93E11 Filtering in stochastic control theory
93B51 Design techniques (robust design, computer-aided design, etc.)
93B36 \(H^\infty\)-control
93A15 Large-scale systems
Software:
YALMIP
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References:
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