Distributed Resilient State Estimation for Fractional-Order State-Saturated Complex Networks with Fading Measurements

In this paper, the distributed resilient state estimation problem is discussed for fractional-order state-saturated complex networks with nonlinearities and fading measurements. The nonlinear function is assumed to satisfy the Lipschitz condition and the fading measurements appear in a stochastic manner with the related coefficients depicted by random variables with known expectations. The distributed resilient estimator gain perturbations are modelled by norm-bounded uncertainties. In particular, based on certain assumption with respect to the cross term of estimation errors, an upper bound (UB) of the estimation error covariance is derived through solving two groups of matrix difference equations. Subsequently, the distributed resilient estimator gain is parameterized by minimizing the trace of the obtained UB. In the end, a numerical simulation is given to verify the validity of the designed distributed resilient state estimation scheme.