Event-triggered state estimation for networked control systems with lossy network communication

This paper investigates the remote state estimation problem for linear stochastic systems with event-triggered communication and packet loss. An event-triggered strategy is designed based on the error between the local information and the remote estimation, then a remote estimation is derived based on the event information. By employing the probability measure space method, the stability and convergence of the expected estimation error covariance (EEC) are proved. In contrast to the previous works on remote estimation with packet loss, the probability measure spaces of EEC are constructed on the event-triggering time steps, and the network resource utilization is reduced while the critical threshold of the tolerable packet loss ratio is still guaranteed. Furthermore, a trade-off condition to design the event-triggering parameters is given. Finally, simulation results are provided to demonstrate the feasibility and the efficiency of the proposed strategy. (C) 2019 Published by Elsevier Inc.