D. Lefebvre

• PhD
• Research Director at Université Le Havre Normandie

Recent research topics have been placed on reinforcing security and safety measures within high-risk industries to protect both equipment and the environment. Numerous industries carry substantial implications for their surroundings. During significant incidents like chemical spills, or nuclear accidents, swiftly gathering precise and dynamic data...

This paper presents a procedure for $K$ -step opacity verification and enforcement of timed observations generated from discrete event systems modeled by time labeled Petri nets. Within the framework of a timed discrete event system that is partially observed by an intruder, a $K$ -step opaque timed observation means that an intruder has observed t...

In this paper, a type of graph, called an extremum timed extended reachability graph, is designed to abstract the temporal specifications and represent the feasible trajectories of time Petri nets. This graph improves the timed extended reachability graph recently proposed for time Petri nets (Lefebvre. Discrete Event Dynamic Systems 29(1):31–56. (...

This article describes a research study on an electromechanical system with saturation, where a fuzzy hybrid controller with integral action and anti-windup is applied. The study focuses on implementing this Integral Fuzzy Logic Controller (IFLC) on a Field-Programmable Gate Array (FPGA) board. The fuzzy controllers, known for their effectiveness i...

This paper addresses the challenge that consists in integrating local short circuits within a global supply chain. This study is motivated by recent changes in the needs of the costumers that are more and more aware about the development of short circuits to facilitate the distribution of products with low carbon emission. More precisely, this pape...

In this paper we investigate a supervisory control problem of discrete event systems under attacks. Specially, we consider a type of sensor deception attacks, called replacement attacks, under which the intruder confuses the observation of events by substituting the occurrence of an observation with another. We use labeled Petri nets as the referen...

This paper addresses fault pattern diagnosis of discrete event systems, involving fault pattern detection and diagnosability. A fault pattern is modelled as a finite automaton whose accepted language is the objective to be diagnosed, representing the occurrence of complex or composite faults. A verifier for fault pattern detection based on the sync...

This paper deals with the optimisation of a multi-robot inspection mission in an industrial area. We aim to solve a specific combinatorial optimisation problem where a team of sensing mobile robots must gather several measurement tasks distributed over the state space. Based on previous work where a Hybrid Filtered Beam Search (HFBS) approach solve...

Recently, considerable attention has focused on enhancing the security and safety of industries with high-risk level activities in order to protect the equipment and environment. In particular, chemical processes and nuclear power generation may have a deep impact on their surroundings. In the case of major events, such as chemical spills, oil rig...

In the last years, Multi-Robot Systems (MRS) have experienced considerable recognition due to various possible real-world applications. Multi-Robot Task Allocation (MRTA) is among the most interesting MRS problems. This problem concerns the situation when a set of given tasks must be performed by a team of mobile robots with the intention of optimi...

This paper offers an operational and methodological response for managing industrial risks by improving the monitoring of industrial areas. The objective is the optimization of monitoring patrols with automated mobile agents that are responsible for the surveillance. Such agents are formed by automated guided vehicles or unmanned aerial vehicles th...

This paper is about the detection of timed patterns for discrete event systems (DESs) that are modeled by a particular class of timed automata. A timed pattern is a set of behaviours characterized by a sequence of events, occurring in a given order and in a given time domain. The problem in which we are interested is to detect the occurrence of suc...

In this paper, a diagnosis problem of discrete event systems (DESs) is considered, including fault pattern detection and diagnosability. A fault pattern in a DES is modeled by an automaton that represents the occurrence of complex faults, i.e., the language of the automaton is the objective to be diagnosed. To solve the problem of fault pattern det...

Temporal aspects of multilevel flow modelling (MFM) are important for reasoning about causes and consequences. In particular real time reasoning about sensor data are dependent on proper temporal ordering of events in order to cope with plant dynamics. The purpose of the present paper is to contribute to the further development of the temporal aspe...

Timed extended reachability graphs (TERG) of time Petri nets abstract the temporal specifications and represent the feasible trajectories under the earliest firing policy. One drawback of such graphs is the rapid increase in the number of states with respect to time specifications. For this reason, approximations of TERG that remove some states hav...

This paper aims to develop a new method to determine a robust scheduling control for systems evolving in uncertain environments. Time Petri Nets with controllable and uncontrollable transitions are used to model the system. The controllable transitions represent the operations and the uncontrollable transitions represent unexpected events that corr...

Chemistry plays an essential role in our modern society [...]

The influence of inlet parameters on the production and thermal risk of complex chemical systems can be cumbersome to evaluate. To determine the optimum safe operating conditions, one needs to solve complex differential equations derived from energy and material balances. This robust approach cannot be made on-site, and it is essential to propose s...

This paper develops design principles for observers of timed discrete event systems that behave according to specific time semantics. Observers devoted to discrete event systems usually ignore the timing aspects of the underlying systems although these aspects can be widely used in many problems, in particular for refinement of estimation and event...

Opacity is a security notion that focuses on determining whether a given system's behavior is kept secret to intruders. Various notions of opacity have received significant attention during the last decade including current state opacity and initial state opacity, which have been studied for deterministic and probabilistic systems in untimed contex...

Safety and risks prevention in numerous industrial domains require a systematic monitoring of areas with high-risk level. The surveillance tasks can be assessed by smart sensor systems. This work is devoted to configure a patrol of mobile robots associated with sets of sensors in order to perform a given sequence of surveillance tasks at minimal co...

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....

An approach is proposed for modeling and scheduling batch production systems based on Petri nets. First, a group of jobs to be carried out by a batch production system is modeled by a transition-timed Petri net according to logical relations between operations and time requirements on operations. Second, conflict relations between operations are ob...

This paper falls under the problems of the monitoring of a Discrete Event System (DES) with time constraints. Among the various techniques used for online and distributed monitoring, we are interested in the chronicle recognition. Chronicles are temporal patterns that represent the system’s possible evolutions. The proposed models are based on P-ti...

Since the early 1990s, considerable efforts have been made in researching and applying approaches for faults detection and diagnosis in chemical processes. The occurrence of chemical accidental events due to thermal runaways have serious consequences for the human, environmental and economic and encourage these efforts. This is the main motivation...

This paper addresses the topic of robust routing and scheduling for parallel systems that suffer from operation interruptions and unreliable resources. The proposed approach uses a partially controllable extension of timed Petri nets as a model of the deterministic and stochastic behaviours. The mean job durations are first evaluated. Then a mean t...

This paper addresses the topic of robust scheduling for flexible manufacturing systems (FMS) with operation interruptions and unreliable resources. The proposed approach uses timed Petri nets as a model of the FMS in uncertain environments. This model includes controllable and uncontrollable transitions. The unexpected firings of the uncontrollable...

The classification and detection of defects play an important role in different disciplines. Research is oriented towards the development of approaches for the early detection and classification of defects in electrical drive systems. This paper, proposes a new approach for the classification of induction motor defects based on image processing and...

Bayesian network (BN) and probabilistic principal component analysis (PPCA) are powerful tools in artificial intelligence. In this study, two intelligent soft sensors, designed based on BN and PPCA, were proposed for fault detection and data prediction in chemical processes. A gas sweetening process was considered as a case study in which the exist...

This article is devoted to the modeling, performance evaluation and robust control of the railway transport network in Sahel Tunisia. The regular increase in the number of passengers makes the management of transportation systems more and more complex. Railway transport requires specific needs. Indeed, many decision and optimization problems occur...

The chemical industry’s activities are often controversial due to the high risks that they represent. Over the past decades, serious industrial events affecting lives, facilities and environment have heightened society's awareness of the negative effects of technology. Among the most hateful events in the chemical industries are the phenomena of th...

Accidental events in chemical industry can cause damages to human health, environment and economy. To prevent such events in industries, it is essential to identify and analyze the past events. To the best of our knowledge, such an analysis has not been done for the French chemical industry sector, which is the second producer in Europe. To fill th...

This paper is about the design of control sequences for discrete event systems (DESs) modeled with bounded partially controlled timed Petri nets (PC-TPNs) including a set of temporal specifications that correspond to minimal firing durations. Petri nets are well-known mathematical and graphical models that are widely used to describe distributed DE...

This paper concerns the design of optimal control sequences for timed Petri nets under earliest firing policy. Optimality is defined with respect to the sequences duration. A method inspired by model predictive control combined with a partial exploration of the reachability graphs of the logical net system underlying the timed PN model is proposed....

This paper is about the performance analysis and control issues for discrete event systems (DESs) including time specifications and modeled with time Petri nets (TPNs). Petri nets are known as efficient mathematical and graphical models that are widely used to describe distributed DESs including choices, synchronizations and parallelisms. The domai...

This paper is about the incremental computation of control sequences for timed discrete events in uncertain environments. The considered uncertainties are the occurrences of uncontrollable events. The domains of application include but are not restricted to flexible manufacturing, communication, computer science, transportation and traffic. Timed P...

This paper concerns the diagnosis of stochastic discrete event systems that behave with non-Markovian dynamics. K-bounded partially observed Petri nets are used to model the system structure and the sensors. Stochastic processes with probability density functions of finite support are used to model the dynamics including some failure processes. The...

This paper is about control design for discrete event systems modeled with Petri nets. It addresses the problems of reachability and of firing sequence design. The untimed and timed cases are successively studied by searching control sequences from an initial marking to a reference one with length or duration that approach the minimal value, avoidi...

This paper studies the fault prognosis of timed stochastic discrete event systems. For that purpose, stochastic Petri nets are considered to model both the healthy and faulty behaviors of the system. Assuming that the possible current markings with their associated probabilities are known, the objective is to estimate the probability of faults occu...

This paper is about fault detection for hybrid dynamical systems modeled with Partially Observed Timed Hybrid Petri Nets (POTHPNs). The marking of some continuous places and the firing of some discrete transitions are assumed to be measured on-line. Abrupt faults are considered as unexpected firings of some discrete silent transitions. From the col...

This article concerns faults detection and isolation for timed stochastic discrete event systems modeled with partially observed timed Petri nets. Events occur according to arbitrary probability density functions. The models include the sensors used to measure events and markings and also the temporal constraints to be satisfied by the system opera...

This paper concerns state estimation of stochastic discrete event systems. For that purpose, partially observed stochastic Petri nets are used to model the system and the sensors. From the proposed modelling and the collected measurements, timed sequences which are consistent with those measurements are obtained. Based on the events date, our appro...

The present study concerns the remote monitoring of immersed plate-like structures as the ones used for marine current turbines. The innovation of this work is the remote damage detection based on a systematic analysis of a small set of ultrasonic measurements limited by the backscattered echoes from the structure edges. The detection and localizat...

This article deals with the problem of fault prognosis in stochastic discrete event systems. For that purpose, partially observed stochastic Petri nets are considered to model the system with its sensors. The model represents both healthy and faulty behaviors of the system. Marking trajectories which are consistent with the measurements issued from...

This paper proposes algorithms that incrementally compute control sequences driving the marking of timed Petri nets from an initial value to a reference one, avoiding forbidden and dangerous states with a duration that approaches the minimal value. The proposed algorithms are applicable to a large class of discrete event systems in particular in th...

This paper is about fault detection and isolation for systems modeled with continuous timed PNs (TCPNs). Abrupt faults and drifts are considered as variations of the TCPN firing parameters. The main contribution is to design and use an observer scheme in order to generate residuals useful for fault detection and isolation issues. A sensor selection...

Parkinson's disease (PD) patients suffers from many disabling syndromes, such as freezing of gait (FoG), handwriting troubles, and speech difficulties. This study describes our methodologies for modeling those PD syndromes based on Bayesian belief network (BBN) formalism. The methodology of the FoG modeling approach is based on data acquired from a...

In this paper, a method for fault occurrence date evaluation in stochastic discrete event systems is proposed. The system is modeled using partially observed stochastic Petri nets. This model includes the faulty behavior that represents the failure processes of the system. From timed observation sequences resulting from this modeling, our approach...

The main contribution of this note is to propose algorithms that incrementally compute control sequences that drive the marking of timed Petri nets from an initial value to a reference one with a duration that approaches the minimal duration. These algorithms are based on a partial exploration of the reachability graph that is inspired from model p...

Preface DCDS provides the communities of safety/reliability analysis and of Discrete Event Systems with an opportunity to exchange information and new ideas, and to discuss new developments in the field of Dependable Control of Discrete Systems. Gathering researchers and practitioners of the two communities, contributes to a better interdisciplin...

Detection and diagnosis method is proposed for surface damage in immersed structures. It is based on noncontact ultrasonic echography measurements, signal processing tools, and artificial intelligence methods. Significant features are extracted from the measured signals and a classification method is developed to detect the echoes resulting from su...

This paper investigates robust adaptive control for unknown non-linear and multivariable systems with fully connected recurrent neural networks. On-line weights updating law and closed loop performance are derived from the Lyapunov approach. Robust stability under the parametric uncertainties due to disturbances of the overall system is provided. T...

This paper addresses the problem of diagnosability for dynamic discrete event systems modeled with bounded or unbounded Petri nets that are deadlock-free and monitored with sensor configurations with marking and event measurements. The proposed method gives necessary and sufficient conditions for diagnosability. It is based on the transformation of...

This paper addresses the control design of Hybrid Dynamic Systems (HDS) modeled by Hybrid Petri Net (HPN) systems. The resolution of the problem is based on Model Predictive Control (MPC). Our goal is to drive a HPN to reach a desired marking. Since HDS incorporates both discrete and continues processes, the proposed control strategy, called Hybrid...

This paper is about trajectory tracking for DESs. The main contribution is to compute incrementally control sequences approaching the minimal length sequences. The method is based on a partial exploration of the PN reachability graph and inspired from the MPC approach. The method is suitable for bounded and unbounded PNs. It also works for PNs with...

This paper presents a new FDI technique for fault detection and isolation in unknown nonlinear systems. The objective of the research is to construct and analyze residuals by means of artificial intelligence and probabilistic methods. Artificial neural networks are first used for modeling issues. Neural networks models are designed for learning the...

The developed method is based on acoustic underwater scattering measurements and can be applied to characterize a defect in a blade of a marine current turbine. To simplify the study, the blade is replaced by a rectangular plate immersed in water having a groove opening out. The measurements are made on horizontal plane perpendicular to the long ax...

This paper addresses the problem of flow variation of timed continuous Petri Nets under infinite server semantics. Our goal is not only to demonstrate the impact of the weighting factor associated to the expression of the flow in the cost function, in reducing flow variation. It is also to find the optimal value and a control optimizing the defined...

This paper addresses the problem of flow variation of Timed Continuous Petri Net (TCPN) systems under infinite server semantics. The problem is studied using Model Predictive Control. Our goal is to find an approach which limits the high flow variation by adding, in the cost function, a new term that takes in consideration these variations and that...