Distributed Secure State Estimation based on multi-Information Selection Detective Mechanism

As the networked control system becomes increasing intelligent, it is essential to realize the operating condition through obtaining real-time states of the system. This paper concentrates on the problem of distributed state estimation under unsecure cyber circumstances with nonlinear dynamics. First, we present an attack detection algorithm utilizing multi-information selection mechanism when there exist attacks in communication channels, based on which a modified distributed extended Kalman filtering algorithm is provided. Then, the filtering parameters are obtained by means of solving upper bounded matrix of estimated error covariance. Finally, we give a numerical example to illustrate the feasibility and effectiveness of our method.