State Estimation For Nonlinear Stochastic System

In this paper, we mainly analyze different types of state estimator for three kinds of nonlinear networked system. The main contents as follows:1) We concern with the non-fragile H∞ state estimation problem for a class of discrete time networked system with probabilistic diverging disturbance and multiple missing measurements. The measurement missing phenomenon is assumed to occur randomly and the missing probability for each sensor. The designed estimator may be sensitive to perturbations. So we design a non-fragile H∞ Estimator. By using the Lyapunov method and stochastic analysis, we derive a sufficient condition for the existence of the desired estimator. By solving the linear matrix inequalities(LMIs), the estimator gain matrix is given. Two numerical examples are employed to demonstrate the effectiveness and applicability of the proposed design technique.2) We investigate event-triggered H∞ state estimation for a class of discrete time neural network with interval time-varying delays and diverging disturbance. The disturbances are diverged between original system and estimator at different diverging rate. The measurement outputs are transmitted to the estimator only when the certain event-triggered condition is met, which can reduce the information communication burden. Some delay-dependent sufficient conditions are derived to guarantee the estimation error system is stochastically stable and the H∞ performance constraint is satisfied. One numerical example is provided to illusion the effectiveness of the proposed methods.3) This paper studies robust Markovian style H∞ state estimation for nonlinear system type with Markovian time delay and randomly occurring cyber attacks. The output data and state are attacked by cyber. Using the Lyapunov method, stochastic analysis, we derive a condition which guarantee estimator such that the dynamics of the estimation error is asymptotically stochastically stable. The desired state estimator is designed to be robust against cyber attacks.The numerical simulation examples are given to illustrate the effectiveness and the feasibility of the theoretical results obtained by the robust control toolbox LMI of MALAB.