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The paper presents a new approach to fuzzy Petri net (FPN) and its hardware implementation. The authors' motivation is as follows. Complex industrial processes can be often decomposed into many parallelly working subprocesses, which can, in turn, be modeled using Petri nets. If all the process variables (or events) are assumed to be two-valued signals, then it is possible to obtain a hardware or software control device, which works according to the algorithm described by conventional Petri net. However, the values of real signals are contained in some bounded interval and can be interpreted as events which are not only true or false, but rather true in some degree from the interval [0, 1]. Such a natural interpretation from multivalued logic (fuzzy logic) point of view, concerns sensor outputs, control signals, time expiration, etc. It leads to the idea of FPN as a controller, which one can rather simply obtain, and which would be able to process both analog, and binary signals. In the paper both graphical, and algebraic representations of the proposed FPN are given. The conditions under which transitions can be fired are described. The algebraic description of the net and a theorem which enables computation of new marking in the net, based on current marking, are formulated. Hardware implementation of the FPN, which uses fuzzy JK flip-flops and fuzzy gates, are proposed. An example illustrating usefulness of the proposed FPN for control algorithm description and its synthesis as a controller device for the concrete production process are presented.

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Using Petri nets (PNs) to control discrete event systems (DES) has many benefits, because of their graphical representations, the possibility of parallel process control, and their formal descriptions. Amongst the different PNs that are applied for this purpose, most have some limitations for visualization. For many of these PNs, another restriction is the length of time between the creation of the control algorithm in the form of a graph and its practical implementation. These two issues can be resolved with one solution called fuzzy interpreted PN (FIPN). This article proposes the use of a program model based on FIPN to control DES and the method for generation of this model using the graphical representation of the net. FIPN offers a better visualization in comparison to discrete PNs and it allows for the quick creation of program code through the application of a simulator called FIPN-SML. This computer tool implements a method that transforms the graphical form of FIPN into Structured Text (ST) language supported by the IEC 61131-3.