Abstract
State estimation is a key requirement for a number of different tasks that arise during the operation, monitoring, and control of a given discrete event system (DES). These tasks include fault diagnosis and event inference, which are directly related to state estimation, as well as supervisory control and optimization/scheduling problems, which are indirectly related to state estimation. This chapter discusses state estimation in DES that are modeled as finite automata with outputs, including the well-studied case of labeled finite automata. In particular, recursive algorithms are described and analyzed for the cases of current-state estimation, delayed-state estimation (smoothing), and initial-state estimation.
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Hadjicostis, C.N. (2020). State Estimation. In: Estimation and Inference in Discrete Event Systems. Communications and Control Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-30821-6_4
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DOI: https://doi.org/10.1007/978-3-030-30821-6_4
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