Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach

This paper is concerned with the distributed filtering problem for a class of delayed nonlinear systems random sensor saturation (RSS) under dynamic event-triggered mechanism. The function assumed to satisfy Lipschitz condition. A mechanism employed further reduce innovation transmission frequencies among adjacent nodes. Both Bernoulli variables and are model phenomenon RSS. aim this design sub-optimal filter such that covariance error has an upper bound, which minimized by appropriately computing gain. Furthermore, boundedness analysed sufficient criterion presented ensure mean-square bounded. Finally, numerical example provided verify effectiveness proposed algorithm.