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A symbolic approach to decentralized set-valued state estimation andprediction for systems that admit a hybrid state machine representations isproposed. The decentralized computational scheme represents a conj unction of afinite number of distributed state machines, which are specified by anappropriate decomposition of the external signal space. It aims at adistribution of computational tasks into smaller ones, allocated to individualdistributed state machines, leading to a potentially significant reduction inthe overall space/time computational complexity. We show that, in general, sucha scheme outerapproximates the state set estimates and predictions of theoriginal monolithic state machine. By utilizing structural properties of thetransition relation of the latter, in a next step, we propose constructivedecomposition algorithms for a recovery of the exact state set outcomes.

Decentralized set-valued state estimation and prediction for hybrid systems: A symbolic approach