The organization level of complex automated robotic and manufacturing systems, whose dynamics is discrete-event dominated, is revisited and some innovative results towards enhancing machine intelligence derived. These comprise a fuzzy-Petri-net reasoning emulator implementing the fuzzy-Petri rule-based decision-making with an appropriate knowledge base support. This fuzzy-Petri reformulation follows the original concept of entropy-based, intelligent machines of G.N. Saridis. Its generic feature in the sense of an improved fuzzy-Petri reasoning based organizing coordination controller is crucial. A software tool emulating the fuzzy-Petri-net reasoning is discussed. Its version employing knowledge-base with 10 rules takes only a few milliseconds on a standard PC to be simulated. Thus it is believed a feasible yet efficient real-time reasoning for supervisory control functions has been developed. Some computer simulations results for FMS applications are given that illustrate these novel developments
Some novel results on a organizing supervisory control, employing fuzzy Petri-net reasoning, along with intelligent communication protocols tailored for flexible manufacturing systems are proposed. Stochastic Petri-net supervisor has been derived via a synergy of fuzzy set and Petri net theories while intelligent communication protocols via object oriented emulation modeling and corresponding programming. These innovative technologies were tested through their application in parallel simulation of medium-size FMS model. Developed representation models have been derived by compatible usage of math-analytical queue, fuzzy Petri-net, and appropriate object-oriented models. Some simulations are presented to illustrate these novel developments
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