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Network models aim to explain patterns of empirical relationships based on mechanisms that operate under various principles for establishing and removing links. The principle of preferential attachment forms a basis for the well-known Barabási–Albert model, which describes a stochastic preferential attachment process where newly added nodes tend to connect to the more highly connected ones. Previous work has shown that a wide class of such models are able to recreate power law degree distributions. This paper characterizes the cumulative degree distribution of the Barabási–Albert model as an invariant set and shows that this set is not only a global attractor, but it is also stable in the sense of Lyapunov. Stability in this context means that, for all initial configurations, the cumulative degree distributions of subsequent networks remain, for all time, close to the limit distribution. We use the stability properties of the distribution to design a semi-supervised technique for the problem of anomalous event detection on networks.

Iterative deadlock prevention strategies based on siphons have drawn increasing attention. For iterative strategies, selecting which siphon to control at each iteration has an influence on the final supervisor in structural complexity, computational complexity, and behavioral permissiveness. In this paper, we define two kinds of emptiable siphons and provide two modified mixed-integer programming (MIP) formulations to compute such siphons. On the basis of them, a three-stage iterative deadlock prevention policy that specifies the siphon control order is proposed. The experimental results show that a supervisor with a simpler structure, higher behavioral permissiveness, and lower computational complexity can be obtained by the proposed strategy since neither the exhaustive siphon enumeration nor the reachability analysis is required.

The automated manufacturing systems (AMS) can be regarded as a resource allocation system which can be abstracted as discrete event systems (DES) for analysis. Once an effective computational method is put forward to the DES, the corresponding real AMS, connected by networks or sensors, can be indirectly controlled. Supervisory control theory (SCT) of DES is developed with the intention of discovering the maximally permissible supervisor of AMS. The state-tree structure (STS) is an extension of SCT, whose application is mainly to solve the SCT state explosion of complicated AMS. The nonblocking supervisory control is investigated on the foundation of predicates in STS, of which the synthesis focuses on the states of the system but ignores the transition between events. In order to effectively solve the above problems, this paper puts forward a novel method based on state feedback control (SFBC) in the STS framework, by which the relation among events is discussed. First, following the definition of the SFBC for predicates, the algorithms to compute the SFBC under reachability, coreachability, and weak controllability are introduced. Second, it is proved that the nonblocking SFBC obtained by the proposed algorithm is equivalent to the one by computing predicates first, which ensures the satisfactory controllers for the supervisory control problems. To demonstrate the contribution of the proposed approach, which is designed considering the symmetry of the system behavior between the real system and its STS model, three examples are illustrated.

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 of discrete event systems modeled by finite state automata. To this end, we revisit the main definitions of diagnosability of intermittent faults, and present comparisons between them, consider verification and analysis techniques, and discuss available complexity results. Examples are used throughout the paper to illustrate the reviewed concepts and verification algorithms. We also look ahead, by suggesting some perspectives for future research. [ABSTRACT FROM AUTHOR]

In this paper, we present a diagnoser‐based approach to deal with fault diagnosis of bounded labeled Petri nets. The approach consists in building a semi‐symbolic diagnoser to analyze diagnosability and perform online diagnosis. The contribution of this paper is twofold: (i) from the theoretical point of view, we provide new conditions for checking diagnosability based on a novel diagnoser variant that explicitly separates the normal reachable markings from the faulty ones, in each diagnoser node. This allows us to independently keep tracking the normal and the faulty diagnoser paths more efficiently. (ii) From the practical point of view and in order to reduce the memory required to build the diagnoser efficiently, we establish a semi‐symbolic encoding of the diagnoser state‐space. Such a representation deploys a symbolic encoding of the diagnoser nodes content, using Binary Decision Diagrams, while it keeps an explicit encoding of the observable transitions between the nodes. In addition, we provide an on‐the‐fly algorithm to simultaneously construct the diagnoser and analyze diagnosability. The effectiveness of the approach is illustrated through some experimentation performed on a Petri net benchmark. [ABSTRACT FROM AUTHOR]

The attitude tracking synchronization control of an orbit-predetermined leader–follower spacecraft swarm for the space moving target is discussed in this paper. The information exchange between all spacecraft is assumed to be discrete in time and on the undirected connected graph. Moreover, due to the demand for saving communication resources, wireless interference has been utilized, which allows all the neighbors of a spacecraft to access the same channel frequency spectrum simultaneously. Then the backstepping control algorithm is designed to let the spacecraft (β,A)-practically stably synchronize their states and track a time-varying trajectory in the presence of unknown fading channels. Finally, simulation is provided to verify that using the proposed control scheme, the attitude tracking synchronization can be achieved with high precision.

Regulation control for Petri nets is a control framework that allows the design of sequence controllers for automation systems in a systematic and efficient way. In order to implement this control framework, the MATLAB® app RCPetri has been developed. In this work, the RCPetri tool functionalities are described, including model generation, automatic specification generation, automatic control design, model and control simulation, automatic translation to PLC code, and communication by Modbus TCP/IP and OPC UA. Furthermore, three examples are presented to illustrate the application of the tool and the regulation framework: an electro-pneumatic device, a process control system, and a robotic manufacturing cell under a decentralized control scheme.

Fault prognosis of discrete event systems (DES) is an active field of research and has become important due to the high demand on systems' safety and reliability. The aim of this paper is to provide the state-of-the-art on fault prognosis of DES, as well as quick directions regarding many aspects of the research on this topic. This overview was carried out using a systematic approach, which allowed us to find and select papers with minimum bias. In total, 74 papers were selected and analyzed in this overview. A classification and an analysis of these papers are made regarding the modeling formalism and decision structure of prognosis of DES. Specific notions of prognosis are also presented. A survey on these papers was performed, regarding practical applications and related problems of prognosis. Results show that most papers present solutions based on languages & automata (56), and most papers consider the centralized decision structure (45). Also, we have found 17 different papers with examples of practical applications of prognosis of DES. We have identified research gaps, such as applications of distributed prognosis and distributed prognosis of Petri nets. Finally, the research activity on prognosis of DES is growing 16.14% by year on average, accordingly to the number of published papers on this topic between 2006 and 2020. [ABSTRACT FROM AUTHOR]

This paper deals with a control problem of discrete event systems subject to capacity constraints. Combined use of timed event graphs and Min-Plus algebra is a well-known approach and efficient for handling timed behavior and mathematical modelling of discrete event systems. However, in current literature, many of control approaches assume that system states are fully observable, which is not the case in our study. Hence, we propose in this paper a feedback control method to guarantee the respect of marking constraints imposed for some paths of partially observable timed event graphs. We demonstrate that if each loop of the considered TEG contains at last one observable transition, we can derive a realisable control law satisfying a set of constraints. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Petri nets are an important tool for creation of new platforms for digitised production systems due to their versatility in modelling discrete event systems. For the development of modern complex production processes for Industry 4.0, using advanced mathematical models based on Petri nets is an appropriate and effective option. The main aim of the proposed article is to design a new software tool for modelling and control of discrete event systems using Arduino-type microcontrollers and code generation techniques. To accomplish this task, a new tool called "PetriNet editor + PetriNet engine" based on Petri nets is proposed able to generate the code for the microcontroller according to the modelled Petri net. The developed software tool was successfully verified in control of a laboratory plant. Offering a graphical environment for the design of discrete event system control algorithms, it can be used for education, research and practice in cyber-physical systems (Industry 4.0). [ABSTRACT FROM AUTHOR]

In order to handle undesirable failures of a multicopter, which occurs in either the pre-flight process or the in-flight process, a failsafe mechanism design method based on supervisory control theory (SCT) is proposed for the semi-autonomous control mode. The failsafe mechanism is a control logic that guides what subsequent actions the multicopter should take, by taking account of real-time information from guidance, attitude control, diagnosis and other low-level subsystems. In order to design a failsafe mechanism for the multicopters, safety issues of the multicopters are introduced. Then, user requirements including functional requirements and safety requirements are textually described, where functional requirements guide the modelling of a general multicopter plant, and safety requirements cover the failsafe measures dealing with the presented safety issues. Based on these requirements, several multicopter modes and events are defined. On this basis, the multicopter plant and control specifications are modelled by automata. Then, a supervisor is synthesized by using SCT. In addition, the authors present three examples to demonstrate the potential conflicting phenomena due to the inappropriate design of control specifications. Finally, based on the obtained supervisor, an implementation method suitable for multicopters is presented, in which the supervisor is transformed into decision-making codes.

A generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.

This paper considers the problem of diagnosability analysis of discrete event systems modeled by labeled Petri nets (LPNs). We assume that the LPN can be bounded or unbounded with no deadlock after firing any fault transition. Our approach is novel and presents the on-the-fly diagnosability analysis using verifier nets. For a given LPN model, the verifier net and its reachability graph (for a bounded LPN) or coverability graph (for an unbounded LPN) are built on-the-fly and in parallel for diagnosability analysis. As soon as a diagnosability decision is established, the construction is stopped. This approach achieves a compromise between computation limitations due to efficiency and combinatorial explosion and it is useful to implement an engineering approach to the diagnosability analysis of complex systems.

A transportation (automotive service) facility location problem is important in urban infrastructure planning and construction. To handle it, researchers have proposed a number of stochastic/random models for locating an automotive service enterprise. However, most of them fail to describe all kinds of uncertainty, e.g., data imprecision. By considering regional constraints, this work proposes a new random fuzzy cost-profit equilibrium model by using uncertainty data and management methods. It presents a hybrid algorithm integrating stochastic fuzzy simulation and particle swarm optimization to solve the location problem of an automobile service enterprise. In addition, since risk factors can impact a decision, this work conducts a risk performance analysis when locating an automotive service enterprise. A practical example is given to illustrate the proposed model and algorithm.

In this paper, we propose a method to design an on-line event feedback supervisor (EFS) for a class of Petri nets whose augmented unobservable subnets are acyclic forward synchronization and backward conflict-free (FSBCF) nets. In more detail, an FSBCF net is an ordinary Petri net in which each place has at most one output transition, and each transition has at most one input place. The designed EFS is able to compute a set of transitions that need to be forbidden based on the current observation of the system. In particular, the EFS is maximally permissive, i.e., it ensures that the controlled system never enters into illegal markings while minimally restricting its behavior. Finally, we use an example to illustrate the effectiveness of the proposed method.

Dynamic reconfiguration techniques can greatly improve the flexibility and reliability of manufacturing systems. However, different from static reconfigurable systems, system behavior during dynamic reconfiguration processes is quite complex due to possible concurrence of system structure changes and events inside unaltered components. This increases the difficulty in designing and developing dynamic reconfigurable systems. The current paper deals with the analysis and control of dynamic reconfiguration process of manufacturing systems from the perspective of discrete event systems. To this end, the authors improve the reconfigurable timed net condition/event systems formalism by assigning reconfiguration functions with extra permeating time, action ranges, and concurrent decision functions. As a consequence, nondeterministic behavior of a dynamic reconfigurable system during dynamic reconfigurations can be specified, while the system correctness, coherence, and safety during reconfigurations can be guaranteed. A reconfigurable manufacturing plant is used as a running example to illustrate the contribution of this paper.

We present majority-based progressive control in which local supervisors have not only their own private specifications as primary goals, but an additional global specification representing a desirable behavior of the overall system. The control policy follows the majority rule, and the ultimate goal is to achieve a progressive closed-loop behavior whereby the number of local supervisors meeting private specifications increases as the controlled system evolves. For this purpose, we present the notion of majority-controllability of a global specification, and show that it is a crucial condition for the existence of local supervisors achieving a progressive global specification. Using the presented control theory, we analyze how the federal estate tax in the Unites States was repealed in 2010. [ABSTRACT FROM AUTHOR]

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, which is a construction that captures all possible k-suffixes of the trajectories that are consistent with a given sequence of measurements that has been recorded. When the system behaves according to Markovian dynamics (i.e., all event occurrences are distributed in time with exponential probability density functions), a parallel-like composition of the timed system with the resulting observer is proposed that leads to a Markovian process. The second contribution is to take advantage of the Markovian analysis to compute certain important characteristic times during which the underlying system should satisfy a given property (based on the suffixes of length k of a given trajectory). To illustrate the approach, we consider two particular properties, namely k-suffix language opacity and k-diagnosability, which can be studied in a stochastic timed context using the Markovian trajectory observer. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper has introduced new formal approaches to model behaviours and control of a class of uncertain timed discrete event systems represented by Timed Automata with Guards (TAGs). We propose alternative representations for Timed Automata with Guards which approximate their dynamics, since only extremal behaviours are considered. More precisely, recursive equations are proposed in (max , +) and (min , +) algebras to describe the worst and the optimistic behaviours. Thereafter, these developed linear models are used to treat a control problem of TAGs. Finally, the proposed methodologies are illustrated by a realistic study case that corresponds to a job-shop system. [ABSTRACT FROM AUTHOR]

At present, no efficient method is proposed for the liveness analysis of general unbounded Petri nets (UPNs) except some of their subclasses. Our previous work presents a non-Karp–Miller finite reachability tree, i.e., lean reachability tree (LRT) to represent their markings. It faithfully expresses and folds the reachability set of an unbounded net. It can totally avoid the efforts made by the existing modified Karp–Miller trees on the expression of potentially unbounded nodes and elimination of all fake markings. By exploiting it, this paper presents a method for comprehensively analyzing the properties of general UPNs. Particularly, we reveal the repeatability of deadlock with the unfolding of some unbounded leaves in LRT and present a sufficient and necessary condition of deadlock existence. Then, LRT and some partial trees generated from it, instead of entire reachability graphs, are utilized to analyze the liveness and reversibility of general UPNs rather than some special ones. The related theoretical results are proven. A unified algorithm based on LRT for analysis of boundedness, liveness, deadlock, and reversibility of general UPNs is developed for the first time. The results of a case study show that the presented method is effective for general UPNs. [ABSTRACT FROM AUTHOR]

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 in investigating opacity. We call opacity under communication delays and losses network opacity. We first define three network opacities: strong network opacity, weak network opacity, and network non-opacity. We derive necessary and sufficient conditions for network opacities and develop methods to check network opacities. We then apply network opacity to solve a problem in battery management systems. [ABSTRACT FROM AUTHOR]

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 state space and the loss of information after abstraction. The paper explains the difficulties and proposes solutions, and experimental results show that counterexamples can be computed successfully for several industrial-scale systems. [ABSTRACT FROM AUTHOR]

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, the algorithm iteratively selects components (plants and variables) from a synchronous composition until a least restrictive controllable solution is obtained. This improves on previous results of the authors where abstraction is only performed by the selection of components and not variables. The paper explains the theory of EFSM synthesis and abstraction and its algorithms. An example of a flexible manufacturing system illustrates how the proposed algorithm works to compute a modular supervisor. [ABSTRACT FROM AUTHOR]

Preventing systems from entering to forbidden states is a crucial issue in discrete event systems control. Adding supervisors to the system is a common method to avoid entering to forbidden states. In discrete event systems modeled by Petri net adding a supervisor could be done by means of control places. Since, the time is not considered in designing this supervisor, in presence of uncontrollable transitions adding control places can lead to increase the operation time of the system modeled by timed Petri net. Because, the firing of some transitions is prevented when it is not necessary. So, to design a more efficient controller, we will be required to use time information of the system component. Therefore, in this paper, a method for optimizing the time behavior of a supervised timed Petri net will be proposed. To obtain an efficient operation, some timed places as timer will be added to the net. The time of this timer places is calculated to permit firing of some controllable transitions in order to enter into some weakly forbidden states while entering to forbidden states is prevented. This concept leads to increase the speed of system as well as obtain an acceptable operation. This method can be applied for all systems modeled by Petri nets. The efficiency of proposed approach will be discussed and validated with a case study. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Scheduling a cluster tool with wafer residency time constraints is challenging and important in wafer manufacturing. With a backward strategy, the scheduling problem of such single-robot-arm cluster tools is well-studied in the literature. It is much more challenging to schedule a more general case whose optimal scheduling strategy is not limited to the backward one. This work uses a timed Petri net (PN) to model the dynamic behavior of the system and presents a method to determine the optimal scheduling strategy for the system. Based on its PN model and the obtained strategy, it reveals that the key issue to schedule such a tool is to determine when and how long the robot should wait for. Based on this finding, this work establishes for the first time the necessary and sufficient conditions regarding the existence of an optimal and feasible one-wafer cyclic schedule for single-robot-arm cluster tools. It then formulates a computationally efficient linear program to find it if existing, and finally gives industrial examples to show the application and power of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the liveness analysis and deadlock control for automated manufacturing systems (AMSs) with multiple resource requirements. Such an AMS is modeled by a class of generalized Petri nets called systems of simple sequential processes with multiple resources (S3PMR). It is shown that a deadlock of the considered AMSs can be characterized by the saturation of a structural object in S3PMR, called perfect resource transition-circuit (PRT-circuit). As a consequence, an S3PMR is live if and only if no PRT-circuit is saturated at any reachable marking. To ensure the system liveness, one has to prevent all PRT-circuits from being saturated at all reachable markings. To develop a structurally simple Petri net deadlock controller, we present the concept of an effective transition cover, which is a special subset of PRT-circuits that may be saturated. Then by designing a control place with a proper control variable for each PRT-circuit in an effective transition cover, we obtain a deadlock controller for the system. The needed control variables are determined by an integer linear program. Since the number of PRT-circuits in an effective transition cover is much less than that of all PRT-circuits that need to control, our controller is of small structural size. For an AMS with saturable PRT-circuits, there exists at least a transition cover. An algorithm is presented for checking the effectiveness of transition covers, and transforming noneffective transition covers into effective ones. Finally, some examples are used to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

An optimal production flow control problem of a make-to-stock manufacturing firm with price, cost, and demand uncertainty is studied. The objective of the flow rate control problem is maximizing the average profit that is the difference between the expected revenue and the expected production, inventory holding, and backlog costs. The uncertainties in the system are captured jointly in discrete environment states. In each environment state, the price, cost, and demand take different levels. The transitions between different environment states evolve according to a time-homogenous Markov chain. By using a continuous flow model, the optimal production policy is stated as a state-dependent hedging policy. The performance of the system where the production cost alternates between a high and a low cost level and the demand is either constant or also alternates between a high and a low level is analyzed under the double-hedging policy. According to this policy, the producer produces only when the cost is low and the surplus is between the two hedging levels. However when the backlog is below the lower hedging level, the producer produces with the maximum capacity regardless of the cost. The effects of production cost, production capacity, demand variability, and the dependence of the demand and the cost on the performance of the system are analyzed analytically and numerically. It is shown that controlling the production rate optimally allows producers respond to the fluctuations in price, cost, and demand in an effective way and maximize their profits. [ABSTRACT FROM AUTHOR]

A method for detecting anomalous behaviours is presented for plants represented as condition systems. An anomalous behaviour can be viewed as observed behaviour of a real system (i.e. a robot, manufacturing cell, etc.) that cannot be accounted for by the set of plant models representing the system, even allowing for fault events. This work builds upon previous modular control synthesis techniques for condition systems. [ABSTRACT FROM AUTHOR]

We deal with timed event graphs whose holding times associated with places are variable. Defining a first-in-first-out functioning rule, we show that such graphs can be linearly described in (max,+) algebra. Moreover, this linear representation allows extending the just-in-time control synthesis existing for timed event graphs with constant holding times. An example is proposed in order to illustrate how the approach can be applied as a just-in-time strategy for production lines. [ABSTRACT FROM AUTHOR]

This paper addresses the control problem of Timed Event Graphs (TEGs) with disturbance transitions, which are subject to marking constraints. In these graphical models, disturbances are uncontrollable input transitions and constraints correspond to the maximum limits of tokens in some places which must not be exceeded. An analytical methodology based on the use of Min-Plus formalisms to synthesize feedback control laws that guarantee the concerned constraints is established. For this, Min-Plus linear models describe the dynamic behavior of the TEGs, and marking constraints are represented by inequalities in Min-Plus algebra. Sufficient conditions are defined to verify the existence of feedback control laws guaranteeing constraint satisfaction in disturbed TEGs. To verify the effectiveness of these proposed theoretical approaches, a real case study of a disturbed disassembly system with limited stocks of components is processed. [ABSTRACT FROM AUTHOR]

A performance-based dynamic scheduling model for random flexible manufacturing systems (FMSs) is presented. The model is built on the mathematical background of supervisory control theory of discrete event systems. The dynamic FMS scheduling is based on the optimization of desired performance measures. A control theory-based system representation is coupled with a goal programming-based multi-criteria dynamic scheduling algorithm. An effectiveness function, representing a performance index, is formulated to enumerate the possible outputs of future schedules. Short-term job scheduling and dispatching decisions are made based on the values obtained by optimizing the effectiveness function. Preventive actions are taken to reduce the difference between actual and desired target values. To analyse the real-time performance of the proposed model, a software environment that included various Visual Basic Application® modules, simulation package Arena®, and Microsoft Access® database was developed. The experimentation was conducted (a) to determine the optimum look-ahead horizons for the proposed model and (b) to compare the model with conventional scheduling decision rules. The results showed that the proposed model outperformed well-known priority rules for most of the common performance measures. [ABSTRACT FROM AUTHOR]

Recently, a new architecture for decentralized diagnosis of Discrete Event Systems, called Decentralized Synchronous Diagnosis, has been proposed in the literature. In this scheme, local diagnosers are computed based on the fault-free behavior of the system components, which, in comparison with the classical diagnosis approach, reduces the size of local diagnosers for implementation. Although this method has been successfully implemented, its main drawback is the emergence of an exceeding fault-free language of the system for diagnosis, which reduces the diagnosis efficiency. To circumvent this problem, in this paper, a protocol for Decentralized Synchronous Diagnosis with Coordination (DSDC), which refines the diagnosis status using cluster automata of the local component models, is proposed. The protocol is based on the implementation of local state estimators of the fault-free component models of the system which communicate cluster automata to a coordinator. The indication of the fault occurrence is carried out by the coordinator according to the observed behavior of the system. To do so, communication rules between local state estimators and the coordinator are proposed. The protocol prevents the emergence of an exceeding fault-free language for diagnosis, which guarantees the same diagnosis performance as the traditional monolithic approach. In addition, the implementation of the DSDC in a didactic manufacturing system is presented to illustrate the results. • The proposed scheme has the same efficiency as the traditional monolithic approach. • A new communication protocol between local diagnosers and coordinator is proposed. • The computational cost is, in general, smaller than methods using the global model. • The method is successfully applied to a didactic manufacturing system. [ABSTRACT FROM AUTHOR]

Possessing efficient supervisory control systems is crucial for maintaining the desired operational performance of complex industrial processes. Several challenges face the developers of these systems, such as requiring accurate physical models, dealing with the variability and uncertainty of process operating conditions and coordinating between local controllers to reach desired global performance. This paper proposes an intelligent supervisory control approach based on causal reinforcement learning (CRL) to effectively manipulate the controllers' setpoints of the process in a way that optimizes its key performance indicators (KPIs), thereby improving the energy efficiency of the process. The approach adopts deep reinforcement learning (DRL) to develop an efficient control policy through interaction with a process simulation. The DRL training history is then exploited using interpretable machine learning and process mining to build a discrete event system (DES) model, in the form of a state-event graph. The DES model identifies causal relationships between events and provides interpretability to the control policy developed by the DRL method. The DES discovered is exploited as a Markov decision process to apply the Q-learning algorithm as a CRL supervisor. The supervisor incorporates causal knowledge into its training process, thus improving the DRL control policy developed and identifying the event paths that optimize the process's KPIs. The proposed approach is validated using two heat recovery systems in a pulp & paper mill. It successfully achieves a control policy that reduces energy consumption by up to 15.6% for the first system and 5.02% for the second, compared to the expert's baseline methods. • This paper proposes a novel supervisory control approach for industrial processes. • The approach is based on causal reinforcement learning (CRL). • The approach integrates simulation-based optimization and process mining. • It learns an optimal control policy for recommending controllers' setpoints. • The approach is validated on two heat recovery systems in a pulp & paper mill. [ABSTRACT FROM AUTHOR]

A workflow is a computerized facilitation or automation of a business process, in whole or in part. Workflow Management Systems integrate humans, computer systems, information resources and organizational processes to provide a unified solution. With rapid increases in application domains that use Workflow Management Systems, it is essential to provide comprehensive and formal modelling approaches that can be used by various workflow software product developers to implement such systems. In this paper, a novel approach to modelling workflow systems based on Discrete Event System and Supervisory Control Theory is introduced. Supervisory controllers that are shown to guarantee desirable properties related to the execution of workflow processes are defined. Both centralized and decentralized supervisory controller designs are considered in order to address computational complexity and scalability issues. [ABSTRACT FROM AUTHOR]