Finite-horizon H∞ filtering for time-varying delay systems with randomly varying nonlinearities and sensor saturations

This paper mainly focuses on the H∞ filtering problem for a class of discrete time-varying systems with delays and randomly varying nonlinearities and sensor saturations. Two sets of binary switching sequences taking values of 1 and 0 are introduced to account for the stochastic phenomena of nonlinearities and sensor saturations which occur and influence the dynamics of the system in a probabilistic way. To further reflect the realities of transmission failure in the measurement, missing observation case is also considered simultaneously. By appropriately constructing a time-varying Lyapunov function and utilizing the stochastic analysis technique, sufficient criteria are presented in terms of a set of recursive linear matrix inequalities (RLMIs) under which the filtering error dynamics achieves the prescribed H∞ performance over a finite horizon. Moreover, at each time point k, the time-varying filter parameters can be solved iteratively according to the explicit solutions of the RLMIs. Finally, a numerical simulation is exploited to demonstrate the effectiveness of the proposed filter design scheme.