State-Saturated Recursive Filter Design for Nonlinear Time-Varying Complex Networks Under Sensor Randomly Occurs Saturation

This paper studies the recursive filtering problem for a class of discrete time-varying nonlinear complex network subject to randomly occurring sensor saturations(ROSS) under a dynamic event-triggered strategy. The nonlinear of complex networks are characterized by nonlinear inner coupling and state saturation. The ROSS phenomenon is described by a set of Bernoulli distributed vectors. The problem to be solved is to design a state-saturated recursive filter, such that, in the presence of both state saturation and random sensor saturation, an upper bound is guaranteed on the covariance of the filtering error, and the upper bound is minimized at each time instant. By using the inductive method, the upper bound of the filtering error variance is constructed according to the solution of a set of matrix difference equations. Finally, by designing filter parameters appropriately to minimize this upper bound.