Abstract
In human–machine (HM) systems, the operators’ task load should be dynamically adjusted in accordance to their physiological and psychological status, so-called operator functional state (OFS). In this sense, the HM system behavior becomes hybrid. Petri net and its extensions have been widely used in hybrid system modeling. In this paper, we use a fuzzy inference Petri net (FIPN) to model the HM system and then realize adaptive task allocation (ATA) between human operator and machine. Simulation results demonstrate that the approach of fuzzy inference Petri nets proposed is an effective way in modeling and control of HM hybrid systems.
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