Non-fragile State Estimation for Nonlinear Complex Networks subject to Missing Measurements and Random Delay with Uncertain Probabilities

This paper is concerned with the non-fragile optimal state estimation problem for a class of delayed time-varying complex networks with stochastic coupling parameters and incomplete measurements. Some Bernoulli random variables are introduced to describe the randomly occurring time-delay and incomplete measurements, where the cases of uncertain occurrence probabilities are considered. A random variable obeying the uniform distribution is introduced to describe the stochastic coupling between network nodes. Moreover, a set of zero-mean multiplicative noises is used to describe the parameter perturbations of the estimator gain matrix. Firstly, a new non-fragile state estimator is constructed via the output measurements transmitted to the remote estimator side. Secondly, a recursive upper bound of the estimation error covariance matrix is found by using the inequality processing technique and matrix theory, and the desirable estimator gain matrix which can minimize such obtained upper bound is given. Finally, a simulation example is given to verify the effectiveness of the proposed locally optimal estimation scheme.