Robust state estimation of fractional-order complex networks with parametric uncertainties

This paper deals with the robust state estimation problem of a class of uncertain fractional-order complex networks with norm-bounded parameter uncertainties. Through available scalar output signals, our aim is to design a state estimator to estimate the network states such that the estimation error is globally robustly asymptotically stable for all admissible parameter uncertainties. Based on the stability theory of fractional-order differential systems, a sufficient condition for the existence of the desired estimator gain is derived, and then the explicit expression of such estimator gain is characterized in terms of the solution to linear matrix inequalities. Finally, simulation examples are provided to show the effectiveness of the designed estimator.