To avoid the state-space explosion problem, a set of supervisors may be synthesized using divide and conquer strategies, like modular or multilevel synthesis. Unfortunately, these supervisors may be conflicting, meaning that even though they are individually non-blocking, they are together blocking. Abstraction-based compositional nonblocking verification of extended finite automata provides means

This paper studies the scheduling problem for the manufacturing systems with uncertain job duration, and the possibility of planning due-date quotations for critical manufacturing tasks given a fixed contingency budget. We propose a due-date quotation model to measure the risk of delay in the manufacturing process in terms of the allocated contingency budget. The risk of delay is measured in the same

The synthesis of controllers for reactive systems can be done by computing winning strategies in two-player games. Timed (game) Automata are an appropriate formalism to model real-time embedded systems but are not easy to use for controller synthesis for two reasons: i) timed models require the knowledge of the precise timings of the system; for example, if an action must occur in the future, the deadline

Karp and Miller’s algorithm is based on an exploration of the reachability tree of a Petri net where, the sequences of transitions with positive incidence are accelerated. The tree nodes of Karp and Miller are labeled with ω-markings representing (potentially infinite) coverability sets. This set of ω-markings allows us to decide several properties of the Petri net, such as whether a marking is coverable

The relevance and presence of Electric Vehicles (EVs) are increasing all over the world since they seem an effective way to fight pollution and greenhouse gas emissions, especially in urban areas. One of the main issues related to EVs is the necessity of modifying the existing infrastructure to allow the installation of new charging stations (CSs). In this scenario, one of the most important problems

We consider the classical problem of minimizing off-line the total energy consumption required to execute a set of n real-time jobs on a single processor with a finite number of available speeds. Each real-time job is defined by its release time, size, and deadline (all bounded integers). The goal is to find a processor speed schedule, such that no job misses its deadline and the energy consumption

One of the challenges in the design of supervisors with optimal throughput for manufacturing systems is the presence of behavior outside the control of the supervisor. Uncontrollable behavior is typically encountered in the presence of (user) inputs, external disturbances, and exceptional behavior. This paper introduces an approach for the modeling and synthesis of a throughput-optimal supervisor for

Nonblocking is an important issue in supervisory control of discrete event systems. In this paper, we investigate nonblocking control for networked discrete event systems. In networked discrete event systems, there are two types of supervisory controls: nondeterministic control and deterministic control. Following the deterministic control, we investigate the nonblocking control problem in a decentralized

This paper proposes a state estimation technique in a decentralized context for time dependent systems. The plant of the studied system is modeled by P-time labeled Petri nets (P-TLPN) and the set of events is partitioned into a set of observable and unobservable ones, leading to a partial observation configuration. Indeed, the observation is distributed over a set of distinct sites which have their

Real life experience has shown that intermittent faults are among the most challenging kinds of faults to detect and isolate, being present in the majority of production systems. Such a concern has made intermittent fault an active area of research in both discrete event and continuous-variable dynamic systems. In this paper, we present a review of the state-of-the art of intermittent fault diagnosability

Let {X(t);t ≥ 0} be a continuous-time branching-immigration system with branching rates {bk; k ≥ 0,k≠ 1} and immigration rates {ak; k ≥ 1}. We assume that b0 = 0, \(m=:{\sum }_{k=1}^{\infty }kb_{k}<\infty \) and \(a=:{\sum }_{k=1}^{\infty }ka_{k}<\infty \). In this paper, we first discuss the martingale property of W(t) = e−mtX(t) − m− 1a(1 − e−mt) and prove that it has a limit W. Furthermore, we show

Systems prone to faults are often equipped with a controller whose aim consists in restricting the behaviour of the system in order to perform a diagnosis. Such a task is called active diagnosis. However to avoid that the controller degrades the system in view of diagnosis, a second objective in terms of quality of service is usually assigned to the controller. In the framework of stochastic systems

The aim of this paper is the generation of the min-critical and max-critical subsystems which determine the optimal cycle times. Considering a Time Interval Model which can describe Timed Event Graphs and P-time Event Graphs completely, each critical subsystem depends on the lower and upper bounds of the time durations. The proposed approach which is based on linear programming makes a classification

Timed Event Graphs (TEGs) are a graphical model for decision free and time-invariant Discrete Event Systems (DESs). To express systems with time-variant behaviors, a new form of synchronization, called partial synchronization (PS), has been introduced for TEGs. Unlike exact synchronization, where two transitions t1,t2 can only fire if both transitions are simultaneously enabled, PS of transition t1

It has been shown that, under some service policies, a queueing network can be unstable even if the load of every station is less than one. Although the stability of queueing systems in some special cases (e.g. under First-Buffer-First-Served policy) has been well addressed, there are still difficulties in coping with more general networks. In this paper, we study the stability problem through depicting

In this paper, we formalize and solve a state-based Supervisory Control problem with restrictions on the supervisor realization that have not been tackled by the Supervisory Control Theory (SCT) community so far. This problem was derived from the application of SCT to intervene in the dynamics of gene regulatory networks, a relevant problem in the fields of Systems and Synthetic Biology. In our framework

The original version of this article unfortunately contained a mistake the last two lines in Table 1 of ‘Appendix H’ should be moved to the next page of the table.

The development, in the last decades, of technologies for precision agriculture allows the acquisition of crop data with a high spatial resolution. This offers possibilities for innovative control and raises new logistics issues that may be solved using discrete event models. In vineyards, some technologies make it possible to define zones with different qualities of grapes and sort the grapes at harvest

In this paper, we shall formulate and address a problem of covert actuator attacker synthesis for cyber-physical systems that are modeled by discrete-event systems. We assume the actuator attacker partially observes the execution of the closed-loop system and is able to modify each control command issued by the supervisor on a specified attackable subset of controllable events. We provide straightforward

In this paper we discuss scheduling of semi-cyclic discrete-event systems, for which the set of operations may vary over a limited set of possible sequences of operations. We introduce a unified modeling framework in which different types of semi-cyclic discrete-event systems can be described by switching max-plus linear (SMPL) models. We use a dynamic graph to visualize the evolution of an SMPL system

A common approach to controller synthesis for hybrid systems is to first establish a discrete-event abstraction and then to use methods from supervisory control theory to synthesise a controller. In this paper, we consider behavioural abstractions of hybrid systems with a prescribed discrete-event input/output interface. We discuss a family of abstractions based on so called experiments which consist

Designing supervisory controllers for high-tech systems is becoming increasingly complex due to demands for verified safety, higher quality and availability, and extending functionality. Supervisor synthesis is a method to automatically derive a supervisor from a model of the plant and a model of the control requirements. While supervisor synthesis is an active research topic, only a few reports exist

This paper presents an algorithm that combines modular synthesis for extended finite-state machines (EFSM) with abstraction of variables by symbolic manipulation, in order to compute least restrictive controllable supervisors. Given a modular EFSM system consisting of several components, the proposed algorithm synthesises a separate supervisor for each specification component. To synthesise each supervisor

Detectability is a basic property of dynamic systems: when it holds an observer can use the current and past values of the observed output signal produced by a system to reconstruct its current state. In this paper, we consider properties of this type in the framework of discrete-event systems modeled by labeled Petri nets and finite automata. We first study weak approximate detectability. This property

It has been shown that annotating Petri nets unfoldings with time stamps allows to build distributed testers for distributed systems. However, the construction of the annotated unfolding of a distributed system currently remains a centralized task. In this paper we extend a distributed unfolding technique in order to annotate the resulting unfolding with time stamps. This allows distributed construction

We study decentralized diagnosis whose objective is fault detection in discrete event systems using decentralized architectures. We first identify a basic diagnosis and two virtual diagnoses as the simplest language-based decentralized diagnosis architectures. The virtual diagnoses cannot be used alone, they are provided to be combined with other diagnoses. On the other side, inference-based diagnosis

Various aspects of privacy and safety in many application domains can be assessed based on proper analysis of successive measurements that are collected about a given system. This work is devoted to such issues in the context of timed stochastic discrete event systems (DES) that are modeled with partially observed timed stochastic Petri net models. The first contribution is to introduce a k-step trajectory-observer

This paper describes algorithms to compute a counterexample when compositional nonblocking verification determines that a discrete event system is blocking. Counterexamples are an important feature of model checking that explains the cause of a detected problem, greatly helping users to understand and fix faults. In compositional verification, counterexamples are difficult to compute due to the large

Timed Event Graphs (TEGs) can be described by time invariant (max,+) linear systems. This formalism has been studied for modelling, analysis and control synthesis for decision-free timed Discrete Event Systems (DESs), for instance specific manufacturing processes or transportation networks operating under a given logical schedule. However, many applications exhibit time-variant behaviour, which cannot

This work is concerned with the computation of problematic configurations and problematic choice-join pairs in timed continuous Petri nets under the infinite server semantics; those net structural objects explain possible bad/counter-intuitive behaviors of systems, such as non-monotonicities and discontinuities of the equilibrium throughput. The calculation of problematic configurations is a computationally

The greedy strategy is an approximation algorithm to solve optimization problems arising in decision making with multiple actions. How good is the greedy strategy compared to the optimal solution? In this survey, we mainly consider two classes of optimization problems where the objective function is submodular. The first is set submodular optimization, which is to choose a set of actions to optimize

Opacity is an important property in control of information flow among networked agents. In this paper, we investigate information control problems in networked discrete event systems using opacity. In a networked discrete event system, communication among agents is via a shared communication network. Since delays and losses are unavoidable in networked discrete event systems, they must be considered

It is a well known fact that not all max-plus automata can be determinized, i.e. transformed into deterministic max-plus automata with the same behavior. A classical sequentialization procedure, extended in the literature to max-plus automata, succeeds in computing an equivalent deterministic max-plus automaton for important subclasses of max-plus automata. This procedure is based on the normalization

We extend Stochastic Flow Models (SFMs), used for a large class of discrete event and hybrid systems, by including the delays which typically arise in flow movements, as well as blocking effects due to space constraints. We apply this framework to the multi-intersection traffic light control problem by including transit delays for vehicles moving from one intersection to the next and possible blocking

Reactive synthesis and supervisory control theory both provide a design methodology for the automatic and algorithmic design of digital systems from declarative specifications. The reactive synthesis approach originates in computer science, and seeks to synthesise a system that interacts with its environment over time and that, doing so, satisfies a prescribed specification. Here, the distinguishing

The objective of this paper is to provide a concise introduction to the max-plus algebra and to max-plus linear discrete-event systems. We present the basic concepts of the max-plus algebra and explain how it can be used to model a specific class of discrete-event systems with synchronization but no concurrency. Such systems are called max-plus linear discrete-event systems because they can be described

This research proposes an automatic strategy for planning a team of identical robots evolving in a known environment. The robots should satisfy a global task for the whole team, given in terms of a Linear Temporal Logic (LTL) formula over predefined regions of interest. A Robot Motion Petri Net (RMPN) system is used for modeling the evolution of the robotic team in the environment, bringing the advantage

Real-world PLC software is modular and composed of many different function blocks. Nevertheless, common approaches to PLC software verification do not leverage this but resort to inlining, or analyse instances of the same function block type independently. With the advent of constrained Horn clauses as the basis for automated program verification, many state-of-the-art verification procedures build

Temporal logics for control of dynamical systems have the potential to automatically synthesize controllers under complex goals expressed by temporal logic formulas. In this paper, we are interested in the situation, where a controller system that implements high and low level controllers is connected to a plant over a communication network. In such control architecture, it is known that the limited

The paper mentioned in the title proposed a new definition of increasing repetitive input sequences for synchronized Petri nets and stated that it can be used to construct a finite modified coverability graph for any unbounded SynPN. In this note, we discuss the notion of unboundedness for SynPNs and show via an example that actually the modified coverability graph may be infinite due the presence

In this paper, we propose a novel dynamic decision method by applying the sensitivity-based optimization theory to find the optimal energy-efficient policy of a data center with two groups of heterogeneous servers. Servers in Group 1 always work at high energy consumption, while servers in Group 2 may either work at high energy consumption or sleep at low energy consumption. An energy-efficient control

This paper considers the finite-horizon risk-sensitive optimality for continuous-time Markov decision processes, and focuses on the more general case that the transition rates are unbounded, cost/reward rates are allowed to be unbounded from below and from above, the policies can be history-dependent, and the state and action spaces are Borel ones. Under mild conditions imposed on the decision process’s

Monoid actions of trace monoids over finite sets are powerful models of concurrent systems—for instance they encompass the class of 1-safe Petri nets. We characterise Markov measures attached to concurrent systems by finitely many parameters with suitable normalisation conditions. These conditions involve polynomials related to the combinatorics of the monoid and of the monoid action. These parameters

This study presents a novel discrete-event systems (DES) modeling framework to address real-time system (RTS) with sporadic, periodic, and non-repetitive real-time tasks. Our approach is organized in three steps. First, the effect of individual timing parameters of each task, such as job arrival and deadlines, are represented by modular DES. Second, we choose the required modules for the specific RTS

Optimization of industrial processes such as manufacturing cells can have great impact on their performance. Finding optimal solutions to these large-scale systems is, however, a complex problem. They typically include multiple subsystems, and the search space generally grows exponentially with each subsystem. In previous work we proposed Compositional Optimization as a method to solve these type of

Fluid-relaxation-based scheduling is a powerful scheduling method for complex resource allocation systems and other stochastic networks. However, this method has been pursued through rather ad hoc representations and arguments in the past. This paper establishes that timed-continuous Petri nets provide a structured and natural framework for the implementation of this method in the context of complex

The modeling of dynamic systems is frequently hampered by a limited knowledge of the system to be modeled and by the difficulty of acquiring accurate data. This often results in a number of uncertain system parameters that are hard to incorporate into a mathematical model. Thus, there is a need for modeling formalisms that can accommodate all available data, even if uncertain, in order to employ them

Nowadays, Web services allow interoperability among distributed software applications deployed on different platforms and architectures which in effect plays a major role in electronic businesses. Web services allow organizations to carry out certain business activities automatically and in a distributed fashion. However, in some circumstances, a single service is not able to perform a certain task

An intelligent transportation systems (ITS) is a typical cyber-physical system (CPS) in which physical components, for example, Connected Automated Vehicles (CAVs), are monitored and controlled through a network of cyber and physical components. Such systems, therefore, contain event-driven dynamics along with time-driven dynamics. The proposed discrete-event and hybrid simulation framework based on

We present an energy-efficient thermal-aware real-time global scheduler for a set of hard real-time (HRT) tasks running on a multiprocessor system. This global scheduler fulfills the thermal and temporal constraints by handling two independent variables, the task allocation time and the selection of clock frequency. To achieve its goal, the proposed scheduler is split into two stages. An off-line stage

In this paper, we present a method for discrete event system identification with the aim of fault detection. The method is based on a new model called Deterministic Automaton with Outputs and Conditional Transitions (DAOCT), which is computed from observed fault-free paths, and represents the fault-free system behavior. In practice, a trade-off between size and accuracy of the identified automaton

This work seeks to develop (lower) performance bounds for a traffic scheduling problem that arises in many application contexts, ranging from industrial material handling and robotics to computer game animations and quantum computing. In a first approach, the sought bounds are obtained by applying the Lagrangian relaxation method to a MIP formulation of the considered scheduling problem that is based

We study sparsity in the max-plus algebraic setting. We seek both exact and approximate solutions of the max-plus linear equation with minimum cardinality of support. In the former case, the sparsest solution problem is shown to be equivalent to the minimum set cover problem and, thus, NP-complete. In the latter one, the approximation is quantified by the ℓ1 residual error norm, which is shown to have

We present the explicit construction of a stable queue with several servers and impatient customers, under stationary ergodic assumptions. Using a stochastic comparison of the (multivariate) workload sequence with two monotonic stochastic recursions, we propose a sufficient condition of existence of a unique stationary state of the system using Renovation theory. Whenever this condition is relaxed

We develop new estimators for the parameters of Ornstein-Uhlenbeck processes driven by compound Poisson processes, which can be considered as a class of stochastic hybrid systems. Our estimators are derived based on the method of moments. We also establish the central limit theorem for the proposed estimators. Numerical experiments are provided to show that our method performs better when compared

Timed weighted marked graphs are a mathematical formalism suitable to model automated manufacturing systems in which synchronization and bulk services and arrivals appear, such as assembly lines and kanban systems. In this paper, we aim to develop practically efficient methods for the marking optimization of timed weighted marked graphs, a problem which consists in finding an initial resource assignment

This paper is about control sequences design for Discrete Event Systems (DES) modeled with Time Petri nets (TPN) including a set of temporal specifications. Petri nets are known as efficient mathematical and graphical models that are widely used to describe distributed DES including choices, synchronizations and parallelisms. The domains of application include but are not restricted to manufacturing

This paper studies an optimal ON-OFF control problem for a class of discrete event systems with real-time constraints. Our goal is to minimize the overall costs, including the operating cost and the wake-up cost, while still guaranteeing the deadline of each individual task. In particular, we consider the homogeneous case in which it takes the same amount of time to serve each task and each task needs

A complex multi-state system subject to different types of failures, repairable and/or non-repairable, external shocks and preventive maintenance is modelled by considering a discrete Markovian arrival process with marked arrivals (D-MMAP). The internal performance of the system is composed of several degradation states partitioned into minor and major damage states according to the risk of failure

This paper studies mean maximization and variance minimization problems in finite horizon continuous-time Markov decision processes. The state and action spaces are assumed to be Borel spaces, while reward functions and transition rates are allowed to be unbounded. For the mean problem, we design a method called successive approximation, which enables us to prove the existence of a solution to the