Extended Kalman filter for networked control systems based on measurements summation

In this paper, a new extended Kalman filter is proposed for the state estimation of nonlinear networked control systems. The Extended Kalman filter based on nominal trajectory linearization is re-described as the summation of measurements, the initial value and the nominal state. For the ideal communication scenarios, the proposed EKF-MS obtains the same estimation accuracy as the EKF based on the nominal trajectory in traditional form. For the networked control systems, the EKF-MS method is developed based on the technologies of measurement predict and information compensation. The final simulation examples show the validity and superiority of the proposed method.