Robust energy-to-peak filtering for networked systems with time-varying delays and randomly missing data

This study is concerned with the robust energy-to-peak (l2–l∞) filtering problem for a class of uncertain linear discrete-time networked control systems with time-varying delays and randomly missing data. The system matrices are assumed to reside in a convex polytope, and the time-varying delays appearing in system states are assumed to lie in a given interval. Moreover, the random data missing is supposed to satisfy the Bernoulli random binary distribution. The authors' goal is to design a full-order filter such that the filtering error dynamic system is exponentially mean-square stable for all admissible time delays and randomly missing data while a prescribed l2–l∞ performance is achieved. Sufficient delay- and parameter-dependent conditions for the existence of the filter and for the solvability of the addressed problem are given in terms of a set of linear matrix inequalities. Finally, simulation examples and comparison studies are provided to demonstrate the effectiveness of the proposed approach.