Modeling Of Discrete Event Systems Research Articles

Modular Synthesis of Least Restrictive Controllable and Nonblocking Supervisors with Distinguishers

Abstract This paper proposes algorithms for supervisor synthesis in discrete event system models with distinguishers. Distinguishers are special components responsible to select an enabled event from a group of related refined events. They are a helpful modelling tool, but their use increases the state space and makes supervisor synthesis more difficult. The paper shows how general algorithms for modular or compositional synthesis can be enhanced by considering the special properties of distinguishers. This gives rise to systematic algorithms that compute least restrictive controllable and nonblocking supervisors, while working with only a part of the distinguisher model. A running example of a manufacturing cell illustrates the approach.

Modeling and Control of Discrete-Event Systems with Partial Non-Determinism using Petri Nets

Modeling and Control of Discrete-Event Systems with Partial Non-Determinism using Petri Nets

V-nets, new formalism to manage diagnosis problems in Cyber-Physical Systems (CPS) and industrial applications

Abstract This article presents the new formalism called V-nets as a tool to deal with diagnosis problems of Cyber-Physical Systems (CPS) and industrial processes, situations such as simultaneity of events, partial recognition of event sequences, and false positives. Cyber-Physical Systems (CPS) and industrial processes demand the reliability of its supervisory and control elements, especially in fault detection applications. There are many scenarios in which typical formal models of DES (Discrete Event Systems) do not guarantee by itself a reliable analysis of the circumstances. The simultaneous occurrence of discrete events and false positives are circumstances examined in this paper and the new formalism V-nets is presented as a new tool that can manage the situations described.

A New Modular Petri Net for Modeling Large Discrete-Event Systems: A Proposal Based on the Literature Study

Petri net is a highly useful tool for modeling of discrete-event systems. However, Petri net models of real-life systems are enormous, and their state-spaces are usually of infinite size. Thus, performing analysis on the model becomes difficult. Hence, slicing of Petri Net is suggested to reduce the size of the Petri nets. However, the existing slicing algorithms are ineffective for real-world systems. Therefore, there is a need for alternative methodologies for slicing that are effective for Petri net models of large real-life systems. This paper proposes a new Modular Petri Net as a solution. In modular Petri net, large Petri net models are decomposed into modules. These modules are compact, and the state spaces of these modules are also compact enough to be exhaustively analyzed. The research contributions of this paper are the following: Firstly, an exhaustive literature study is done on Modular Petri Nets. Secondly, from the conclusions drawn from the literature study, a new Petri net is proposed that supports module composition with clearly defined syntax. Thirdly, the new Petri net is implemented in the software GPenSIM, which is crucial so that real-life discrete-event systems could be modeled, analyzed, and performance-optimized with GPenSIM.

Petri Net Based Modeling and Property Analysis of Distributed Discrete Event System

PetriNet is an imperative and handy language used for modeling and analysis of discrete event system (DES) i.e. a dynamic system that progress according to unexpected occurrence of events at probably unknown, asymmetrical interval of time. This concept provides an interface for analysis of behavioral and structural properties like liveness, boundedness and cover-ability tree of discrete event systems. These properties are not only necessary for proving the correctness of system model but also helpful in checking the deadlock conditions in a system. As a graph Petri Net is used for modeling and mathematically, it can be used for analysis of the system. In this paper, we have first modeled various DES like computation model and communication model using Petri Nets and then analyzed their properties using MATLAB. These DES models have applications in almost every domain of science and engineering.

Nonblocking Supervisory Control of State-Tree Structures With Conditional-Preemption Matrices

State-tree structure (STS) is a powerful tool for the modeling and control of large-scale discrete-event systems (DES) whose structure is organized in a top–down hierarchy. The notorious state-explosion problem can be managed effectively in the framework of STS. Priority is an important concept and exists in a wide range of DES, such as manufacturing systems, traffic systems, and logistic (service) systems. In this article, a conditional-preemption matrix is used to describe the preemption relations among events, which can represent the priority intuitively. In order to augment STS with priority, we propose a novel STS framework: STS with conditional-preemption matrices (STSM), which aims to solve different kinds of issues related to priority. The optimal nonblocking supervisory control is deployed in the framework of STSM. Symbolic synthesis algorithms are implemented and integrated in a software tool, STSLib, which exploits binary decision diagrams as a basis for efficient computation. The developed approach is demonstrated by (a) manufacturing systems using automatic guided vehicles and (b) real-time systems.

Supervisors of Petri Nets

Abstract The design and operation of modern industrial systems require modeling and analysis in order to select the optimal design alternative and operational policy. Discrete event system models are encountered in a variety of fields, for example computers, communication networks, manufacturing systems, sensors or actuators, faults diagnosis, robotics and traffic. The paper describes principles and methods of supervisory control of discrete event systems initiated by Ramadge and Wonham. Three supervisory control methods based on the Petri net models are introduced, and the key features of the Petri tool software application for the supervisory control of discrete event systems modeled by Petri nets are highlighted.

Modeling, simulation, estimation and boundedness analysis of discrete event systems

In this paper, a particular state model allowing describing the system evolution in time is proposed. This state model contains two inequalities describing the evolution in time of the system state and input. The system simulation is based on the resolution of this state model. After that, a state estimator is proposed in order to estimate the whole system state and inputs. The state model and the observer are both proposed following count and dater approaches successively. In this work, the considered state is the number of transition firing if a count approach is followed and the dates of firing if the dater approach is considered. It is proved, using an illustrative example, that the proposed observer estimates well the system state by comparing the simulated and the estimated states. A boundedness analysis of the system trajectory is proposed in the case of FCF Petri nets. This analysis is based on an algorithm which gives the bounded transitions knowing the system input. Some particular tables are elaborated to describe the proposed algorithm. Theses tables give the bounded transitions after each iteration of the algorithm.

Discrete Event Systems: Modeling, Observation, and Control

This article begins with an introduction to the modeling of discrete event systems, a class of dynamical systems with discrete states and event-driven dynamics. It then focuses on logical discrete event models, primarily automata, and reviews observation and control problems and their solution methodologies. Specifically, it discusses diagnosability and opacity in the context of partially observed discrete event systems. It then discusses supervisory control for both fully and partially observed systems. The emphasis is on presenting fundamental results first, followed by a discussion of current research directions.

Discrete-Event Systems Modeling and the Model Predictive Allocation Algorithm for Integrated Berth and Quay Crane Allocation

In this paper, we study the problem of integrated berth and quay crane allocation (I-BCAP) in general seaport container terminals and propose the model predictive allocation (MPA) algorithm and preconditioning methods for solving the I-BCAP. First, we propose a dynamical modeling framework based on discrete-event systems (DESs), which describes the operation of a berthing process with multiple discrete berthing positions and multiple quay cranes. Second, based on the discrete-event model, we propose the MPA algorithm for solving the I-BCAP using the model predictive control (MPC) principle with a rolling event horizon. The validation and performance evaluation of the proposed modeling framework and allocation method are done using: 1) extensive Monte Carlo simulations with realistically generated datasets; 2) real dataset from a container terminal in Tanjung Priuk port, located in Jakarta, Indonesia; and 3) real life field experiment at the aforementioned container terminal. The numerical simulation results show that our proposed MPA algorithm can improve the efficiency of the process where the total handling and waiting cost is reduced by approximately 6%–9% in comparison with the commonly adapted method of first-come first-served (FCFS) (for the berthing process) combined with the density-based quay cranes allocation (DBQA) strategy. Moreover, the proposed method outperforms the state-of-the-art hybrid particle swarm optimization (HPSO)-based and genetic algorithm (GA)-based method proposed in the recent literature. The real life field experiment shows an improvement of about 6% in comparison with the existing allocation method used in the terminal.

Fault Identification of Discrete Event Systems Modeled by Petri Nets With Unobservable Transitions

This paper deals with the identification problem of faulty behavior in a discrete event system, assuming that the fault-free model of a system is given in terms of Petri nets, where the set of transitions is divided into two disjoint subsets: 1) observable and 2) unobservable ones. The observed system output is defined as a transition-marking sequence, i.e., each transition is followed by a marking. First, a nonlinear integer programming model that characterizes the faults modeled by fault transitions is built according to the abnormal behavior extracted from the observed sequence. Then, it is converted into an integer linear programming (ILP) problem and a faulty net that preserves the structure of the fault-free one is obtained by solving this ILP model. In addition, an algorithm is developed to ensure acyclicity of the resulting unobservable subnet whose transition set is composed of the unobservable transitions of the fault-free net and the identified fault transitions.

Petri Nets at Modelling and Control of Discrete-Event Systems with Nondeterminism -- Part 2

Discrete-Event Systems (DES) are discrete in nature. Petri Nets (PN) are one of the most widespread tools for DES modelling, analyzing and control. Different kinds of PN can be used for such purposes. Some of them were described in [3], being the first part of this paper. Here, the applicability of Labelled PN (LbPN) and Interpreted PN (IPN) for modelling and control of nondeterministic DES, especially with uncontrollable and/or unobservable transitions in the models, will be pointed out. Moreover, another kinds of nondeterminism in DES (errors, failures) will be modelled, and the possibilities of the error recovery of failed system will be presented.

Diagnosability of Vector Discrete-Event Systems Using Predicates

The diagnosability problem of faults is studied in the framework of vector discrete-event system (VDES). A VDES is a discrete-event system model in which a system state is represented by a vector with integer components, and state transitions are represented by integer vector addition. Predicates are employed to verify the fault diagnosability of VDES, since, defined as functions, predicates can conveniently identify particular state sets of interests. Specifically, system states are partitioned into different subsets by predicates, and the fault diagnosability of a system is verified by checking a subset of states. A sufficient condition for fault diagnosability of VDES is presented first. A necessary and sufficient condition is then developed. According to the two conditions, two types of predicates are given to partition the states in a VDES. In this work, a diagnoser or a full state enumeration is not constructed, whose complexity is exponential with respect to the system state size. In order to verify whether a system satisfies the proposed conditions, several polynomial algorithms and an algorithm by constructing a tree automaton are developed. Several examples are provided to illustrate the results obtained in this paper.

NB-DEVS: a hybrid approach for modelling and simulation of imperfect systems

This article presents the NB-DEVS approach for the modelling and simulation of discrete event systems (DES), our objectives are to propose a new formal approach for describing the complex systems involving imperfectly. In our research we propose to integrate the naïve Bayesian network (NB) into DEVS formalism. The association of these two formalisms we have allow to extend the classic DEVS formalism to new domains. This new approach permits to study the system when its behaviour is uncertain. Finally, we simulated the evolution of the production system using our NB-DEVS approach. In simulation, we used several different models to replicate the empirical data. From these simulation iterations, we were able to verify and validate our model.

NB-DEVS: a hybrid approach for modelling and simulation of imperfect systems

This article presents the NB-DEVS approach for the modelling and simulation of discrete event systems (DES), our objectives are to propose a new formal approach for describing the complex systems involving imperfectly. In our research we propose to integrate the naive Bayesian network (NB) into DEVS formalism. The association of these two formalisms we have allow to extend the classic DEVS formalism to new domains. This new approach permits to study the system when its behaviour is uncertain. Finally, we simulated the evolution of the production system using our NB-DEVS approach. In simulation, we used several different models to replicate the empirical data. From these simulation iterations, we were able to verify and validate our model.

농업용 군집드론 시스템을 제어하기 위한 관리제어기 설계 : 예비결과

A discrete event systems (DES) based approach is an efficient method to control complex dynamic systems. This paper describes a DES which uses supervisory control theory to control multiple. Agricultural unmanned aerial vehicles (UAVs). Finite state automata (FSA) are used as a modeling tool to design a supervisor to coordinate the behavior of multiple UAVs. In this paper, DES models for obstacle avoidance, path following, formation control, and task control are modeled by the FSA and controlled by the supervisor. The proposed supervisors are implemented. Their controllability, nonblocking, and non-conflicting behaviors are verified through simulation. The use of the DES formalism reflects a modular controllable system with the potential for reusability and scalability.

An implementation method for the supervisory control of time-driven systems applied to high-voltage direct current transmission grids

In recent years, the growth of renewable energy production has encouraged the development of new technologies, such as High-Voltage Direct Current (HVDC) networks, that enhance the integration of such energy sources to power transmission grids. However, this type of technology introduces new challenges in the way power transmission systems are controlled and operated, as faster and more complex control strategies will be needed in a domain which nowadays relies heavily on human decisions. In this context, Discrete Event Systems (DES) modeling and Supervisory Control Theory (SCT) are powerful tools for the development of a supervisory control to be deployed in the grid. This paper presents an application of the SCT to HVDC grids and proposes an implementation method for the resulting supervisors. The proposed method is capable of integrating decentralized and discrete-event controllers that interact with the continuous-time physical system. The language chosen for the implementation is C code, as it can be easily incorporated in power system simulation software, such as EMTP-RV. The method is validated by the simulation of the start-up of a point-to-point link in the EMTP-RV software.

Stability Analysis of Discrete Event Systems Modeled by Petri Nets Using Unfoldings

The stability of discrete event systems (DESs) is a property related to its robustness; a stable DES is guaranteed to reach a set of desired states in a finite number of steps. Algorithms proposed in the literature are useful for analyzing the stability of DES modeled either by finite automata or a constrained subclass of Petri nets (PNs). In this paper, a novel method to decide the stability of safe PNs is presented. It is based on the analysis of the finite complete prefix of the net unfolding rather than the reachability graph. For concurrent systems, the prefix is usually smaller than the reachability graph and then the analysis using the proposed algorithm is more efficient than analyzing the reachability set of the PN. Note to Practitioners —The stability of a discrete event system (DES) is a property that guarantees that the DES will return to the normal operation behavior after a disturbance deviates the system from such a behavior. This is a key property that a controlled DES must fulfill. The algorithms proposed in this paper allow determining efficiently the stability of concurrent DES by analyzing the Petri net structure.

SPECIAL ISSUE: Modelling, Simulation, and Control of Discrete Event Systems

SPECIAL ISSUE: Modelling, Simulation, and Control of Discrete Event Systems

Systemic Design Approach to a Real-Time Healthcare Monitoring System: Reducing Unplanned Hospital Readmissions.

Following hospital discharge, millions of patients continue to recover outside formal healthcare organizations (HCOs) in designated transitional care periods (TCPs). Unplanned hospital readmissions of patients during TCPs adversely affects the quality and cost of care. In order to reduce the rates of unplanned hospital readmissions, we propose a real-time patient-centric system, built around applications, to assist discharged patients in remaining at home or in the workplace while being supported by care providers. Discrete-event system modeling techniques and supervisory control theory play fundamental roles in the system’s design. Simulation results and analysis show that the proposed system can be effective in documenting a patient’s condition and health-related behaviors. Most importantly, the system tackles the problem of unplanned hospital readmissions by supporting discharged patients at a lower cost via home/workplace monitoring without sacrificing the quality of care.