Failure detection via recursive estimation for a class ofsemi-Markov switching systems
Campo, L.; Mookerjee, P.; Bar-Shalom, Y.
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Volume , Issue , 7-9 Dec 1988 Page(s):1966 - 1971 vol.3
Digital Object Identifier   10.1109/CDC.1988.194677
Summary:The authors apply the recursive state estimation algorithm for dynamic systems whose state model experiences jumps according to a sojourn-time-dependent Markov (STDM) chain to the problem of failure detection. The algorithm, which is of the interacting-multiple-model (IMM) type, uses noisy state observations. Two simulation examples are presented. The first indicates that the use of the STDM-based IMM estimator can give a substantial improvement in state estimation over a Markov-based IMM. The second example shows that for the particular system under consideration, the STDM-based IMM estimator, which is a hypothesis-merging technique, compares favorably in terms of the probability of error to the detection-estimation-algorithm-based estimator, which discards the unlikely parameter history hypothesis

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