Modeling Of Discrete Event Systems Research Articles

Max-Plus Algebraic Modeling and Control of High-Throughput Screening Systems

In this paper, we present a max-plus algebraic model for cyclically operated high-throughput screening plants. A max-plus algebraic representation of the system, derived directly from a discrete-event systems model of the predetermined globally optimal solution, contains negative order arcs, forcing certain events in previous cycles to occur after events in the current cycle. With respect to the cycle index, though of course not in terms of time, the model is acausal. However, the model can be transformed into a system representation without negative order arcs. The obtained max-plus algebraic model can then be applied as a controller to handle unexpected deviations from the predetermined cyclic operation during runtime.

Performance evaluation of discrete event systems involving Henstock-Kurzweil integral

This paper presents a study on the performance of flexible manufacturing systems (FMSs), by using discrete event system (DES) models, considering resource losses modelled by a parameter entitled coverage factor. We conclude that the resources cell loss distribution between the tasks of a FSM is a real function that cannot be integrated, in order to calculate its primitive, in the classical sense of Riemann or Lebesgue, but only in the sense of Henstock-Kurzweil integral. Our result allows one to study more general processes where highly oscillatory functions occur. The method used to deduce the function describing the resources cell loss distribution is compared with a classical method related in the literature, respectively rational interpolants. An example has been constructed to emphasize what we believe to be, new approaches.

Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB

The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System Specification (DEVS) and model predictive control (MPC) modeling approaches. To formulate the interactions between the discrete process model and its controller, another model called Knowledge Interchange Broker (KIB) is used. A robust and scalable testbed supporting DEVS-based manufacturing process modeling, MPC-based controller design, and the KIBDEVS/MPC interaction model is developed. A suite of experiments have been devised and simulated using this testbed. The flexibility of this approach for modeling, simulating, and evaluating stochastic discrete process models under alternative control schemes is detailed. The testbed illustrates the benefits and challenges associated with developing and using realistic manufacturing process models and process control policies. The simulation environment demonstrates the importance of explicitly defining and exposing the interactions between the manufacturing and control subsystems of complex semiconductor supply-chain systems.

Interactive evolutionary modelling and simulation of discrete-event systems using prototypical objects

In this paper, we describe an alternative approach to the traditional class-based approach of building simulation models using object-oriented languages. We use the Discrete EVent Systems specification (DEVS) formalism implemented by prototypical objects. The main reason why we use prototype-based object orientation for simulation modelling is the fact that it offers the level of flexibility that we need for interactive evolutionary modelling and simulation, which is used for simulation-based development of systems without exact specifications. We introduce a reflective framework model that constructs, inspects and edits the models specified using DEVS. The meta-object protocol of this framework allows the models to be constructed from scratch and inspected and edited during run-time. Interactive evolutionary modelling and simulation is supported by a visual tool set which has been highly influenced by the user interface of Self, an object-oriented language based on prototypical objects.

A Meta-Model Based Approach for Definition of a Multi-Formalism Modeling Framework

Many software tools and environments are developed for modeling discrete-event systems. Although, most of the existing tool are proposed for modeling with one or a few modeling languages. In this paper, we propose a meta-modeling approach for definition of a multi-formalism modeling framework for Petri nets and related formal modeling languages. The proposed framework and the related software tool facilitate the inclusion of formalisms in the framework in a unified manner. The proposed meta-modeling structure is designed in four layers such that the most abstract layer as the meta-formalism and the least abstract layer as the concrete model. The basic concepts of the meta-modeling structure and some examples of formalisms are presented based on the proposed structure. We explain the techniques and the architecture of the implemented tool based on the proposed meta-modeling structure for the framework.

Diagnosability of fair discrete event systems

AbstractFailure diagnosability has been widely studied using discrete event system (DES) models. It is, however, shown in this work by means of a counterexample that the diagnosability condition, which has been shown to be necessary and sufficient in the DES context, fails to hold for many real‐world hybrid systems. This is because the abstraction employed in formulating the DES models obliterates the continuous dynamics. In the present work, a new failure diagnosability mechanism has been developed for discrete time hybrid system (DTHS) models to alleviate this problem. A new diagnosability condition is proposed and its necessity and sufficiency with respect to the diagnosability definition are established formally. Finally, the method of A‐diagnosability, which can also be used to circumvent this problem and which needs additional probabilistic information for diagnosability analysis, has been shown to have a higher computational complexity than the DTHS model based method proposed in this paper. Further, it is also highlighted that the DTHS model based diagnosability analysis technique is capable of diagnosing faults that degrade the temporal performance of the system, which cannot be handled by the A‐diagnosability analysis mechanism. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Expressiveness of verifiable hierarchical clock systems

The modelling and analysis of multi-component discrete event systems is a challenging research area. Over 30 years, modelling and simulation research of discrete event system specification (DEVS) has been developed with (1) dense-time, (2) the I/O concept, and (3) hierarchical model construction. Nevertheless, DEVS model verification research began relatively recently considering the whole DEVS research history. In the meantime, over 15 years, the automata theory has been developed to cover the dense-time behaviour verification of discrete event systems. Especially, timed automata (TA) has performed the key role in the field. This paper builds on the research results that have been achieved from both theories of DEVS and TA. Thus contributions of this paper can be seen from each side. From the viewpoint of the DEVS theory, a finite and nondeterministic DEVS has been found as a verifiable class. From the viewpoint of the TA theory, a TA which is modular and hierarchical as well as verifiable, is proposed. To show the results, this paper uses the top down manner in which a general formalism is defined first and then its sub-classes are introduced.

Modeling time-varying uncertain situations using Dynamic Influence Nets

This paper enhances the Timed Influence Nets (TIN) based formalism to model uncertainty in dynamic situations. The enhancements enable a system modeler to specify persistence and time-varying influences in a dynamic situation that the existing TIN fails to capture. The new class of models is named Dynamic Influence Nets (DIN). Both TIN and DIN provide an alternative easy-to-read and compact representation to several time-based probabilistic reasoning paradigms including Dynamic Bayesian Networks. The Influence Net (IN) based approach has its origin in the Discrete Event Systems modeling. The time delays on arcs and nodes represent the communication and processing delays, respectively, while the changes in the probability of an event at different time instants capture the uncertainty associated with the occurrence of the event over a period of time.

Robust supervisory control of fuzzy discrete event systems

The authors investigate a robust supervisory control problem based on the model of fuzzy discrete event systems. If there are uncertainties in the systems, the model can be assumed to belong to a model set. For all possible models in the set, necessary and sufficient conditions for the existence of a supervisor to achieve the given fuzzy language specification are obtained under complete and partial observations. The relation between the controllability (and observability) with respect to the models and their upper bound is given, based on which the equivalent conditions for the existence of a supervisor are obtained.

Modeling of asynchronous discrete-event systems as networks of input-output automata

A new approach for component-oriented modeling of asynchronous discrete-event systems is presented where input-output (I/O) automata are used for representing the components. Coupling signals are introduced to describe the interactions among the components. The resulting network of I/O-automata has a direct correspondence to the block diagram. By using the parallel composition rule known from standard automata modeling as an example, it is shown that the new model is applicable for at least the same class of asynchronous discrete-event systems as the known modeling formalisms.

Modelling and scheduling projects using Petri nets

This paper addresses the modelling suitability of Petri Nets (PNs) for project planning and control. PNs, while being vastly used for the modelling and analysis of discrete event systems, were scarcely mentioned in the context of project management. This paper familiarises the readers with PNs and illuminates its modelling advantages. Next, the PN suitability for modelling and scheduling a project is discussed. Finally, a new PN type, called the Petri Project Net (PPN), is proposed and it best addresses the special features required by project scheduling problems, including the practical implications for scheduling and resource planning in an uncertain environment.

Integrating Temporal Logic as a State-Based Specification Language for Discrete-Event Control Design in Finite Automata

This paper presents and analyzes a correct and complete translation algorithm that converts a class of propositional linear-time temporal-logic (PTL) formulae to deterministic finite (-trace) automata. The translation algorithm is proposed as a specification interface for finitary control design of discrete-event systems (DESs). While there has been a lot of computer science research that connects PTL formulae to omega-automata, there is relatively little prior work that translates state-based PTL formulae in the context of a finite-state DES model, to event-based finite automata-the formalism on which well-established control synthesis methods exist. The proposed translation allows control requirements to be more easily described and understood in temporal logic, widely recognized as a useful specification language for its intuitively appealing operators that provide the natural-language expressiveness and readability needed to express and explain these requirements. Adding such a translation interface could therefore effectively combine specifiability and readability in temporal logic with prescriptiveness and computability in finite automata. The former temporal-logic features support specification while the latter automata features support the prescription of DES dynamics and algorithmic computations. A practical implementation of the interface has been developed, providing an enabling technology for writing readable control specifications in PTL that it translates for discrete-event control synthesis in deterministic finite automata. Two application examples illustrate the use of the proposed temporal-logic interface. Practical implications of the complexity of the translation algorithm are discussed.

Diagnosis of delay–deadline failures in real time discrete event models

In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

Modeling and analysis using hybrid Petri nets

This paper is devoted to the use of hybrid Petri nets (PNs) for modeling and control of hybrid dynamic systems (HDS). Modeling, analysis and control of HDS attract ever more of researchers’ attention and several works have been devoted to these topics. We consider in this paper the extensions of the PN formalism (initially conceived for modeling and analysis of discrete event systems) in the direction of hybrid modeling. We present, first, the continuous PN models. These models are obtained from discrete PNs by the fluidification of the markings. They constitute the first steps in the extension of PNs toward hybrid modeling. Then, we present two hybrid PN models, which differ in the class of HDS they can deal with. The first one is used for deterministic HDS modeling, whereas the second one can deal with HDS with nondeterministic behavior.

DES modelling and control vs. problem solving methods

Modelling and control of a kind of Discrete-Event Systems (DES) having a character of Flexible Manufacturing Systems (FMS) are examined by means of methods used in applied artificial intelligence. While assembly and/or disassembly processes are controlled by means of the problem solving methods (the so called block world and the Hanoi tower puzzle), the process of crossing vehicles inside FMS is controlled as the multi-agent system. Petri Net (PN)-based models are utilised in order to described the dynamic behaviour of the systems. The control strategy based on Reachability Graphs (RGs) is proposed and illustrated. Feasible state trajectories in the space of feasible states are found. The set of discrete events corresponding to particular segments of the trajectories represents the result of control synthesis.

QUALITATIVE ANAYSIS OF THE BDSPN MODEL THROUGH ITS ASSOCIATED DISCRETE PETRI NET

The BDSPN model is a class of Petri nets introduced for the modelling, analysis and performance evaluation of discrete event systems with batch behaviours. It is particularly suitable for the modelling of flow evolution in batches of variable sizes in a system with activities performed in batch modes. In this paper, the analysis of the BDSPN model through its associated discrete Petri net is studied. It is shown that although a BDSPN and its associated discrete Petri net behave differently, there are several common qualitative properties between the two models.

PROBABILISTIC FAULT DIAGNOSIS IN DISCRETE EVENT SYSTEMS WITH INCOMPLETE MODELS

Most model-based approaches to fault diagnosis require a complete model of the system. When the model is incomplete, system outputs may be inconsistent with the model, stopping the diagnosis process. In this paper, a probabilistic approach combined with model learning is used to diagnose a system with an incomplete discrete event system model. When an inconsistency arises, probabilistic abductive inference is used to learn improved models of the system. To improve the efficiency of model learning, a tabu search scheme is developed. The improved models are combined with the system outputs for probabilistic diagnosis.

Online Fault Diagnosis of Discrete Event Systems. A Petri Net-Based Approach

This paper is concerned with an online model-based fault diagnosis of discrete event systems. The model of the system is built using the interpreted Petri nets (IPN) formalism. The model includes the normal system states as well as all possible faulty states. Moreover, it assumes the general case when events and states are partially observed. One of the contributions of this work is a bottom-up modeling methodology. It describes the behavior of system elements using the required states variables and assigning a range to each state variable. Then, each state variable is represented by an IPN model, herein named module. Afterwards, using two composition operators over all the modules, a monolithic model for the whole system is derived. It is a very general modeling methodology that avoids tuning phases and the state combinatory found in finite state automata (FSA) approaches. Another contribution is a definition of diagnosability for IPN models built with the above methodology and a structural characterization of this property; polynomial algorithms for checking diagnosability of IPN are proposed, avoiding the reachability analysis of other approaches. The last contribution is a scheme for online diagnosis; it is based on the IPN model of the system and an efficient algorithm to detect and locate the faulty state. Note to Practitioners-The results proposed in this paper allow: 1) building discrete event system models in which faults may arise; 2) testing the diagnosability of the model; and 3) implementing an online diagnoser. The modeling methodology helps to conceive in a natural way the model from the description of the system's components leading to modules that are easily interconnected. The diagnosability test is stated as a linear programming problem which can be straightforward programmed. Finally, the algorithm for online diagnosis leads to an efficient procedure that monitors the system's outputs and handles the normal behavior model. This provides an opportune detection and location of faults occurring within the system

SYNTHESIS OF SUPERVISORS FOR PARAMETERIZED AND INFINITY NON-REGULAR DISCRETE EVENT SYSTEMS

This article presents a model for discrete-event systems in which the plant consists of a finite State Transition System, or STS, equipped with a data collection. The data collection introduces variables whose values are updated by operations commanded by the discrete transitions in the STS. The specifications of desirable behaviors consist of predicates related to the occurrence of the events. The supervisor, based on the sequence of events occurred in the past, controls the system evolution through the disabling of events. The decision of disabling events originates from the evaluation of predicates computed from the specification of desirable behaviors. A method for the synthesis of supervisors attaining a specification with minimally restrictive control is presented. The main characteristics of our framework are the possibility of capturing non-regular behaviors and the construction of parameterized models which lead to generic solutions for a given class of problems.

CONFLICTS AND PROJECTIONS

This paper studies abstraction methods suitable to verify very large models of discrete-event systems to be nonconflicting. It compares the observer property to methods known from process algebra, namely to conflict equivalence and observation equivalence. The observer property is shown to be the property that corresponds to conflict equivalence in the case where natural projection is used for abstraction. In this case, the observer property turns out to be the least restrictive condition that can be imposed on natural projection to enable compositional reasoning about conflicts. The observer property is also shown to be closely related to observation equivalence. Several examples and propositions are presented to relate different aspects of these methods of abstraction.