Complex Discrete Event Systems Research Articles

Nonblocking supervisory control of state-tree structures with event forcing

For complex discrete-event systems, state-tree structures (STSS) have demonstrated significant advantages in terms of the modeling and supervisor synthesis. The notorious state explosion problem can be effectively managed in STS. In this paper, the STS framework is enhanced with the concept of event forcing. Intuitively, event forcing is utilized to deny permission for the occurrence of undesirable competing events, that is, such events are directly or indirectly disabled. To reflect event forcing in STS, a systematic on-the-fly procedure during supervisor synthesis is proposed, which benefits the computational effort of computer memory and time cost. In addition, an incrementally iterative algorithm is developed and the computational complexity of it is polynomial with respect to the number of binary decision diagram nodes in use. Finally, several case studies are provided for evaluating the performance of the method. The experimental results show that the proposed method is computationally efficient for supervisor synthesis of a discrete-event system imposed event forcing.

Fault Diagnosis in Partially Observed Petri Nets Using Redundancies

This paper is devoted to the development of an approach to the diagnosability of a system described in the framework of partially observed Petri nets (POPNs) such that the developed fault diagnosis technique can be widely applicable to systems with mutable initial states and partial observations. Existing studies show that the diagnosability of a discrete event system (DES) can be improved by suitable sensor selections or redundancies. This paper proposes a redundancy-building method for a POPN with a certain sensor selection such that no matter how the POPN is initially marked, it achieves maximally structural diagnosability, i.e., the diagnosability of a system cannot be further improved based on the given sensor selection and knowledge of the plant model, which is critical and fundamental in fault recovery capabilities for operating large and complex DESs. To make the proposed method practically applicable, we do not require prior knowledge of faults or special structure of a system, instead we model faults as abnormal events occurring on transitions or places in the plant but not special transitions. Necessary and sufficient conditions for maximally structural diagnosability of a system are established. Redundancies (externally observable places) that guarantee behavior permissiveness and maximally structural diagnosability are built by solving integer linear programming problems.

Modelado de compras verdes mediante redes de Petri coloreadas

Los países desarrollados han implementado políticas de desarrollo sostenible específicamente en Consumo y Producción Sustentable. El proceso de compras verdes suele ser considerado crítico para el adecuado rendimiento de la cadena de suministro porque gestiona y garantiza la adquisición de los productos/servicios para que la empresa cumpla con sus actividades misionales, generando beneficios económicos, mitigando los efectos de sus actividades en el medio ambiente y en la sociedad. Este artículo presenta un modelo para el proceso de compras verdes, basada en una herramienta para la modelación de sistemas de eventos discretos complejos llamada Redes de Petri Coloreadas (RdPC).

Container – Terminal – Gate – System Optimization

The utility of the container terminal has become quite remarkable all over the world. It is vital to maximize the utility of the container yard and the terminal gate system. With the ever-increasing importance of containerization in the world, more than 60% of cargo is transported by containers, this ratio even reaches 100% in some highly economic developed and political stable places. It is estimated that, the total quantity of containerization in the world will increase by 10% every year before 2020. The aim of this work is to be used as a decision support system tool when designing and constructing container terminals. The article focuses on optimizing the staging of containers within a terminal gate system. A Port within the main Land China is being used as a test bed to demonstrate the Simulation Model based on Queuing Theory. The analysis considers both the facility and the setting of the terminal gate system by considering the Discrete Event System Theory and the terminal gate system in order to make the daily operation more suitable for the terminal. The research combines the computer simulation method and the actual complex discrete event system, and identifies the most suitable setting and the theoretical maximum capacity for the terminal. Normally, the usage ratio (the busy time) should be around 75%, the simulation findings, the channel performance measures indicators are the usage ratio and the average waiting time the proper number of channel is 3 for entrance channel, and 2 for exit channel with usage ratios of 74% and exit usage of 55%, allocating 3 Entrance Channel (gates) and 2 Exit Channels (gates). Both the entrance and exit saved 2 channels. Both the capacity and channel number calculation are treated as a reference for the future decision maker when it comes to the container terminal construction.

Formal Approach to Control Design of Complex and Dynamical Systems

In this paper, we tackle the design of complex discrete event systems whose structures change as they are developed in different operating modes. Based on the Supervisory Control Theory (SCT), we propose a formal hierarchical approach for controlling the design of these systems by using a multi-model approach; it involves representing complex systems by a set of simple models, each of which describing the system in a given operating mode. The resulting framework allows resolving problems of reconfigurations and managing of common components to multiple operating modes; and it is designed by using the Colored Petri Nets (CP-Nets) formalism.

A Modular Colored Stochastic Petri Net for Modeling and Analysis of Signalized Intersections

The dynamic behavior of traffic lights regulating a network of intersections can be viewed as a complex discrete-event system that can be modeled and controlled by Petri nets. In this paper, a bilayer signalized control method is presented. In the lower layer, a colored stochastic Petri net controls the signal indication displays and stage transitions. In the upper layer, a supervisory logic layer decides which stage should be serviced next. The proposed model increases modularity, reduces complexity, and, more importantly, is capable of being used to implement various signal control strategies. The method is used to implement four different control strategies: pretimed control, fully actuated control, semiactuated control, and random stage selection (as a benchmark) in the context of a signalized traffic network containing six intersections. Extensibility and future potential research to further enhance the proposed method are discussed and proposed at the end.

Diagnosis of Active Systems by Semantic Patterns

A gap still exists between complex discrete-event systems (DESs) and the effectiveness of the state-of-the-art diagnosis techniques, where faults are defined at component levels and diagnoses incorporate the occurrences of component faults. All these approaches to diagnosis are context-free, in as much diagnosis is anchored to components, irrespective of the context in which they are embedded. By contrast, since complex DESs are naturally organized in hierarchies of contexts, different diagnosis rules are to be defined for different contexts. Diagnosis rules are specified based on associations between context-sensitive faults and regular expressions, called semantic patterns. Since the alphabets of such regular expressions are stratified, so that the semantic patterns of a context are defined based on the interface symbols of its subcontexts only, separation of concerns is achieved, and the expressive power of diagnosis is enhanced. This new approach to diagnosis is bound to seemingly contradictory but nonetheless possible scenarios: a DES can be normal despite the faulty behavior of a number of its components; also, it can be faulty despite the normal behavior of all its components.

Compositions of (max, +) automata

This paper presents a compositional modeling approach by means of (max, +) automata. The motivation is to be able to model a complex discrete event system by composing sub-models representing its elementary parts. A direct modeling of safe timed Petri nets using (max, +) automata is first introduced. Based on this result, two types of synchronous product of (max, +) automata are proposed to model safe timed Petri nets obtained by merging places and/or transitions in subnets. An asynchronous product is finally proposed to represent particular bounded timed Petri nets.

An Efficient Multiple Fault Detection and Isolation Scheme for Discrete Event System

The malfunction of sensors, actuators, and erroneous actions of human operators can have some disastrous consequences in high risk systems especially if these systems have multiple faults that can lead to undesirable shutdowns and consequently a plant output reduction. This paper introduced a new scheme to detect and isolate multiple faults in complex discrete event systems. This scheme comprises a set of discrete rules and an inference engine. The former characterizes the dynamic behavior of a process that is modeled by a Petri net and the latter infers the consequent part of the fired rules. The consequent parts are aggregated and compared with the original Petri net model of the process for detecting multiple faults. The proposed inference engine follows the forward reasoning strategy that fires transitions from the initial marking until the final marking is reached. Industrial processes are employed for testing the soundness of the proposed scheme.

Graphical modeling and simulation of discrete-event systems with CD++Builder

We introduce CD++Builder, an open-source environment that aims at providing easy-to-use graphical modeling tools to simplify the construction of models and the execution of simulations of complex Discrete Event System Specification (DEVS) models. The architecture and implementation of CD++Builder focuses on providing simple definition and reuse of components, offering easy extensibility to support new features. CD++Builder includes graphical editors for DEVS-coupled models, DEVS-Graphs and C++ atomic models; it provides code templates that are synchronized with their graphical versions, and it greatly simplifies the software installation and update procedures. We show how this environment can be used to build and simulate DEVS models, and we compare the process with previous versions and other simulation tools, showing that CD++Builder can improve model development by creating DEVS models in a completely assisted manner, including advanced graphical interfaces.

A modular Petri net to modeling and scenario analysis of a network of road traffic signals

The dynamic behavior of a group of traffic signals controlling a network of intersections is a complex discrete event system that can be modeled by Petri nets. The approach used in this paper proposes a components-based design, which increases modularity, reduces complexity and is a good practice according to modern Systems Engineering. The main system elements are specified based on the proposed Petri net component with time intervals associated to places. The specified models are simulated through the common token player algorithm, and formal analysis using invariants and theorem proving are applied to verify models' soundness and to reason on specific scenarios.

Using infinitesimal perturbation analysis of stochastic flow models to recover performance sensitivity estimates of discrete event systems

Stochastic Flow Models (SFMs) form a class of hybrid systems used as abstractions of complex Discrete Event Systems (DES) for the purpose of deriving performance sensitivity estimates through Infinitesimal Perturbation Analysis (IPA) techniques when these cannot be applied to the original DES. In this paper, we establish explicit connections between gradient estimators obtained through a SFM and those obtained in the underlying DES, thus providing analytical evidence for the effectiveness of these estimators which has so far been limited to empirical observations. We consider DES for which analytical expressions of IPA (or finite difference) estimators are available, specifically G/G/1 and G/G/1/K queueing systems. In the case of the G/G/1 system, we show that, when evaluated on the same sample path of the underlying DES, the IPA gradient estimators of states, event times, and various performance metrics derived through SFMs are, under certain conditions, the same as those of the associated DES or their expected values are asymptotically the same under large traffic rates. For G/G/1/K systems without and with feedback, we show that SFM-based derivative estimates capture basic properties of finite difference estimates evaluated on a sample path of the underlying DES.

Perturbation Analysis and Optimization of Multiclass Multiobjective Stochastic Flow Models

Stochastic Flow Models (SFMs) are stochastic hybrid systems that abstract the dynamics of complex discrete event systems involving the control of sharable resources. SFMs have been used to date to study systems with a single user class or some multiclass settings in which performance metrics are not class-dependent. In this paper, we develop a SFM framework for multiple classes and class-dependent performance objectives in which we can analyze new, occasionally counterintuitive, phenomena and give rise to a new type of “induced” events that capture delays in the SFM dynamics. In the case of two classes, we derive Infinitesimal Perturbation Analysis (IPA) estimators for their derivatives and use them as the basis for on-line optimization algorithms that apply to the underlying discrete event system (not the SFM). This allows us for the first time in the use of SFMs to contrast system-centric and user-centric objectives.

Using Infinitesimal Perturbation Analysis of Stochastic Flow Models to Recover Performance Sensitivity Estimates of Discrete Event Systems

AbstractStochastic Flow Models (SFMs) form a class of hybrid systems used as abstractions of complex Discrete Event Systems (DES) for the purpose of deriving performance sensitivity estimates through Infinitesimal Perturbation Analysis (IPA) techniques when these cannot be applied to the original DES. In this paper, we establish explicit connections between gradient estimators obtained through a SFM and those obtained in the underlying DES, thus providing analytical evidence for the effectiveness of these estimators which has so far been limited to empirical observations. We consider DES for which analytical expressions of IPA (or finite difference) estimators are available, specifically G/G/1 and G/G/1/K queueing systems. We show that, when evaluated on the same sample path of the underlying DES, the IPA gradient estimators of states, event times, and various performance metrics derived through SFMs are, under certain conditions, the same as those of the associated DES or their expected values are asymptotically the same under large traffic rates.

Définition d'un modèle de pilotage pour un jeu à récit interactif. Gestion de l'exécution adaptative du déroulement d'une application interactive

This paper aims at defining a software architecture that allows managing an adaptive unfolding of an interactive application such as a game. This architecture basis comes from the one of complex discrete event system control. This paper begins by introducing the general software architecture for games underlying the two main approaches (scenario oriented and emergent). Then the specificities of games are described. It comes from the difficulty to allow the player to have significant impact on the game unfolding without changing the plot structure define a posteriori. Finally an example of a game is given in order to validate a multi-level architecture.

CONFLICTS AND FAIR TESTING

This paper studies conflicts from a process-algebraic point of view and shows how they are related to the testing theory of fair testing. Conflicts have been introduced in the context of discrete event systems, where two concurrent systems are said to be in conflict if they can get trapped in a situation where they are waiting or running endlessly, forever unable to complete their common task. In order to analyse complex discrete event systems, conflict-preserving notions of refinement and equivalence are needed. This paper characterises an appropriate refinement, called the conflict preorder, and provides a denotational semantics for it. Its relationship to other known process preorders is explored, and it is shown to generalise the fair testing preorder in process-algebra for reasoning about conflicts in discrete event systems.

Comparison of selection rules for ordinal optimization

The evaluation of performance of a design for complex discrete event systems through simulation is usually very time consuming. Optimizing the system performance becomes even more computationally infeasible. Ordinal optimization (OO) is a technique introduced to attack this difficulty in system design by looking at “order” in performances among designs instead of “value” and providing a probability guarantee for a good enough solution instead of the best for sure. The selection rule, known as the rule to decide which subset of designs to select as the OO solution, is a key step in applying the OO method. Pairwise elimination and round robin comparison are two selection rule examples. Many other selection rules are also frequently used in the ordinal optimization literature. To compare selection rules, we first identify some general facts about selection rules. Then we use regression functions to quantify the efficiency of a group of selection rules, including some frequently used rules. A procedure to predict good selection rules is proposed and verified by simulation and by examples. Selection rules that work well most of the time are recommended.

Diagnosability of Discrete Event Systems with Modular Structure

The diagnosis of unobservable faults in large and complex discrete event systems modeled by parallel composition of automata is considered. A modular approach is developed for diagnosing such systems. The notion of modular diagnosability is introduced and the corresponding necessary and sufficient conditions to ensure it are presented. The verification of modular diagnosability is performed by a new algorithm that incrementally exploits the modular structure of the system to save on computational effort. The correctness of the algorithm is proved. Online diagnosis of modularly diagnosable systems is achieved using only local diagnosers.

An On-line Simulation Approach to Search Efficient Values of Decision Variables in Stochastic Systems

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event system. The proposed algorithm in this paper searches the effective and reliable alternatives satisfying the target values of the system to be designed through a single run in a relatively short time period. It tries to estimate an auto-regressive model, and construct mean and confidence interval for evaluating correctly the objective function obtained by a small amount of output data. The experimental results using the proposed method are also shown.

A DECENTRALIZED MODEL-BASED DIAGNOSTIC TOOL FOR COMPLEX SYSTEMS

We address the problem of diagnosing complex discrete-event systems such as telecommunication networks. Given a flow of observations from the system, the goal is to explain those observations by identifying and localizing possible faults. Several model-based diagnosis approaches deal with this problem but they need the computation of a global model which is not feasible for complex systems like telecommunication networks. Our contribution is the proposal of a decentralized approach which permits to carry out an on-line diagnosis without computing the global model. This paper describes the implementation of a tool based on this approach. Given a decentralized model of the system and a flow of observations, the program analyzes the flow and computes the diagnosis in a decentralized way. The impact of the merging strategy on the global efficiency is demonstrated and illustrated by experimental results on a real application.