Time-varying and steady-state Kalman predictors for descriptor system with random d-step transmission delay and packet dropout

In networked systems, data packets are transmitted through networks from a sensor to a data processing center. Due to the unreliability of communication channels, a packet may be delayed even lost during the transmission. Therefore, this paper is concerned with the time-varying and steady-state Kalman prediction problem for descriptor systems with d-step random transmission delays and packet dropout. First of all, applying the singular value decomposition (SVD) method and the fictitious noise approach, the original descriptor system is transformed to new standard system only with fictitious noises. Based on this system, time-varying and steady-state Kalman predictors are proposed by using the projection theory. The convergence of the proposed steady-state Kalman predictors are analyzed. To verify the conclusion presented in this paper, a simulation example has been shown.