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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
YALMIP
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