The paper deals with an automatic concurrent control design method derived from the specification of a discrete event control system represented in the form of a decision table. The main stages of our approach are: the control specification by decision tables, generation of rules from the specification of the system behavior, and converting rules set into a concurrent program represented in the form of a Petri net. Our approach is based on rough set theory.
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Signal-event nets provide a modular modeling technique based on Petri nets. Actions of a module can be activated or can be prevented by another module through condition arcs. One-sided synchronization of modules is done by signal-events, which cause the execution of actions in steps. But due to condition arcs and signal-events simultaneous firing of steps may lead to markings, which are not reachable by conventional sequential interleaving. We give a criterion, in which situations simultaneous firing of steps can be safely omitted, without missing reachable markings.
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Petri nets have a longstanding history in controller design and implementation, and it is often told that they have the dominating position in this field due to the close relationship between Petri nets and Graphcet or other sequential function diagrams. We want to show that there are some severe problems when Petri nets are used to describe both: the controller and the plant under control. The nature of these problems is the lack of a concept of input and output signals and, moreover, the lack of a formal concept to interconnect systems modeled by Petri nets via signals. Although this is often neglected, it turns out to be a key issue if a model of the closed-loop behavior must be established as a precondition for formal controller verification. We present a signal extension for Petri nets and means for interconnecting an arbitrary number of those extended Petri nets. We come up with the conclusion that the resulting models are suited for controller verification. Although the graphical appearance shows similarities to Petri nets, the resulting models are no longer Petri nets.
Design of control sequences for discrete event systems (DESs) has been presented modelled by untimed Petri nets (PNs). PNs are well-known mathematical and graphical models that are widely used to describe distributed DESs, including choices, synchronizations and parallelisms. The domains of application include, but are not restricted to, manufacturing systems, computer science and transportation networks. We are motivated by the observation that such systems need to plan their production or services. The paper is more particularly concerned with control issues in uncertain environments when unexpected events occur or when control errors disturb the behaviour of the system. To deal with such uncertainties, a new approach based on discrete time Markov decision processes (MDPs) has been proposed that associates the modelling power of PNs with the planning power of MDPs. Finally, the simulation results illustrate the benefit of our method from the computational point of view.
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This paper presents a constrained decomposition methodology with output injection to obtain decoupled partial models. Measured process outputs and decoupled partial model outputs are used to generate structured residuals for Fault Detection and Isolation (FDI). An algebraic framework is chosen to describe the decomposition method. The constraints of the decomposition ensure that the resulting partial model is decoupled from a given subset of inputs. Set theoretical notions are used to describe the decomposition methodology in the general case. The methodology is then detailed for discrete-event model decomposition using pair algebra concepts, and an extension of the output injection technique is used to relax the conservatism of the decomposition.
Fleet systems are considered complex due to the interaction between their units and components. Maintenance management systems face various challenges to achieve acceptable availability and reliability rates at a reasonable cost. A critical task for making maintenance decisions is understanding the system requirements to select maintenance policies appropriate for the actual and future system state. When there is a replacement shortage in a fleet system, and it is impossible to supply new spare parts quickly, cannibalization policies can mitigate this scarcity via the interchange of components. However, this procedure presents the maintenance manager with different evaluation effects, such as increased maintenance hours, decreased system reliability rate, and unavailability in some units. Finding an equilibrium between the benefits and risks has caught the attention of researchers. This work gathers diverse proposals for applying cannibalization policies and the effects that arise from using them. Models, methods, tools, and identified gaps in understanding what parameters of the components and environments of the fleet systems favor cannibalization are discussed.
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Motivated by the integrated complexity of real-time intelligent control and optimization of industrial/manufacturing processes, this paper discusses hybrid modelling and asymptotic periodic behavior of a class of switched discrete event systems, and shows how to evaluate the asymptotic performance/efficiency of such systems. We prove that, under some mild conditions, the switched discrete event system will achieve asymptotic periodic dynamics, and its performance/efficiency can be evaluated by calculating the eigenvalue of certain matrix in max-plus algebra. Illustrative examples are provided.
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