Stochastic analysis and control of real-time systems with random time delays
Automatica (Journal of IFAC)
H∞ filtering for multiple-time-delay measurements
IEEE Transactions on Signal Processing
Hidden Markov model state estimation with randomly delayedobservations
IEEE Transactions on Signal Processing
Automatica (Journal of IFAC)
Kalman filtering for multiple time-delay systems
Automatica (Journal of IFAC)
Robust filtering for discrete time piecewise impulsive systems
Signal Processing
Decentralized robust set-valued state estimation in networked multiple sensor systems
Computers & Mathematics with Applications
Digital Signal Processing
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This paper is concerned with the dynamic Markov jump filters for discrete-time system with random delays in the observations. It is assumed that the delay process is modeled as a finite state Markov chain. To overcome the difficulty of estimation caused by the random delays, the single random delayed measurement system is firstly rewritten as the multiplicative noise constant-delay system. Then, by applying the measurement reorganization approach, the system is further transformed into the delay-free one with Markov jump parameters. Finally, the estimator is derived by using the standard Markov jump filter theories. It is interesting to show that the presented filter for the system with random jump delays can be designed by performing two sets of standard Riccati equations with the same dimension as that of the original system. A simulation example is given to illustrate the effectiveness of the proposed result.