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A distributed Kalman filter with event-triggered communication and guaranteed stability. (English) Zbl 1400.93296
Summary: The paper addresses Kalman filtering over a peer-to-peer sensor network with a careful eye towards data transmission scheduling for reduced communication bandwidth and, consequently, enhanced energy efficiency and prolonged network lifetime. A novel consensus Kalman filter algorithm with event-triggered communication is developed by enforcing each node to transmit its local information to the neighbors only when this is considered as particularly significant for estimation purposes, in the sense that it notably deviates from the information that can be predicted from the last transmitted one. Further, it is proved how the filter guarantees stability (mean-square boundedness of the estimation error in each node) under network connectivity and system collective observability. Finally, numerical simulations are provided to demonstrate practical effectiveness of the distributed filter for trading off estimation performance versus transmission rate.

MSC:
93E11 Filtering in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93E15 Stochastic stability in control theory
93B07 Observability
93C65 Discrete event control/observation systems
90B18 Communication networks in operations research
93-04 Software, source code, etc. for problems pertaining to systems and control theory
93A14 Decentralized systems
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