Linear estimation for random delay systems. (English) Zbl 1222.93143
Summary: This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on the Kalman filtering technique. However, the optimal filter is time-varying, stochastic, and does not converge to a steady state in general. Then an alternative suboptimal filter with deterministic gains is developed under a new criteria. The estimator performance in terms of their error covariances is provided, and its mean square stability is established. Finally, a numerical example is presented to illustrate the efficiency of proposed estimators.
MSC:
| 93C55 | Discrete-time control/observation systems |
| 93E11 | Filtering in stochastic control theory |
| 93E15 | Stochastic stability in control theory |
Keywords:
linear estimation; random delay; reorganized innovation analysis; Riccati equation; convergence; stabilityReferences:
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