Robust \(H_\infty \) Filtering of Stochastic Switched Complex Dynamical Networks with Parameter Uncertainties, Disturbances, and Time-Varying Delays

摘要

This paper investigates the problem of stability analysis for switched complex dynamical networks with mixed time-varying delays and parameter uncertainties. The switched complex dynamical networks are composed of m modes that are switched from one to another based on time, state, etc. Although, the active subsystem is known in any instance, but the switching law such as transition probabilities are not known. The model for each mode is considered affine with matched and unmatched perturbations. The main purpose of the addressed problem is to design a filter error for the switched complex dynamical networks such that the dynamics of the error converges to the asymptotically irrespective of the admissible parameter variations with the gains. Then, by utilizing the Lyapunov functional method, the stochastic analysis combined with the matrix inequality techniques, a sufficient condition in terms of linear matrix inequalities is presented to ensure the \(H_\infty \) performance of the complex dynamical system models. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design method.