Event-Triggered Set-Membership State Estimation for Discrete Delayed Linear Systems over Sensor Networks

This paper discusses the event-triggered set-membership state estimation problem for discrete delayed linear systems over sensor networks, where noises are unknown but bounded. For the purpose of saving limited communication resources between sensor nodes, a novel adaptive dynamic event-triggered mechanism is applied to reduce the frequency of data transmission. Based on the topological structure of sensor networks and the event-triggered condition, a distributed set-membership state estimator is designed to ensure that the states and estimation errors are restricted within the corresponding zonotopes. The appropriate gain matrices of the estimator are selected to minimize the F-radius of the zonotopes, where the augmented estimation error is located at every instant. In order to avoid the huge computational load caused during the estimation iteration process, the reduction operator is introduced to find a compromise between the conservative of the zonotopic estimation results and the complexity of operation. Finally, a numerical example is offered to demonstrate the effectiveness of the proposed event-triggered zonotopic set-membership state estimation algorithm.