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— In an earlier paper [1], we introduced the notion of safety control of stochastic discrete event systems (DESs), modeled as controlled Markov chains. Safety was specified as an upper bound on the components of the state probability distribution, and the class of irreducible and aperiodic Markov chains were analyzed relative to this safety criterion. Under(More)
— We study the control of completely observed Markov chains with safety bounds as introduced in [3], but with more general safety constraints and the added requirement of optimality. In [3], the safety bounds were specified as unit-interval valued vector pairs (lower and upper bounds for each component of the state probability distribution). In this paper(More)
We study the control of completely observed Markov chains subject to generalized safety bounds and optimality requirement. Originally, the safety bounds were specified as unit-interval valued vector pairs (lower and upper bounds for each component of the state probability distribution). In this paper, we generalize the constraint to be any linear convex set(More)