Optimal linear estimation with square-based sampling

This paper is concerned with the problem of event-based sampling for the purpose of reducing the number of data transferred in control systems and the corresponding modified Kalman filter. A mathematical description based upon square-based sampling is proposed, in which the sampling occured when the accumulated difference between two adjacent sampling points satisfies the specified event condition. Then, by utilizing the square based sampling method, a modified Kalman filter algorithm is adopted, in which the measurement is sent when the output exceeds a given event. The simulation results illustrate the advantage of the new event-based sampling scheme and the effectiveness of modified Kalman filter.