362 research outputs found

    Fast Discrete Consensus Based on Gossip for Makespan Minimization in Networked Systems

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    In this paper we propose a novel algorithm to solve the discrete consensus problem, i.e., the problem of distributing evenly a set of tokens of arbitrary weight among the nodes of a networked system. Tokens are tasks to be executed by the nodes and the proposed distributed algorithm minimizes monotonically the makespan of the assigned tasks. The algorithm is based on gossip-like asynchronous local interactions between the nodes. The convergence time of the proposed algorithm is superior with respect to the state of the art of discrete and quantized consensus by at least a factor O(n) in both theoretical and empirical comparisons

    A new approach for diagnosability analysis of Petri nets using Verifier Nets

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    In this paper, we analyze the diagnosability properties of labeled Petri nets. We consider the standard notion of diagnosability of languages, requiring that every occurrence of an unobservable fault event be eventually detected, as well as the stronger notion of diagnosability in K steps, where the detection must occur within a fixed bound of K event occurrences after the fault. We give necessary and sufficient conditions for these two notions of diagnosability for both bounded and unbounded Petri nets and then present an algorithmic technique for testing the conditions based on linear programming. Our approach is novel and based on the analysis of the reachability/coverability graph of a special Petri net, called Verifier Net, that is built from the Petri net model of the given system. In the case of systems that are diagnosable in K steps, we give a procedure to compute the bound K. To the best of our knowledge, this is the first time that necessary and sufficient conditions for diagnosability and diagnosability in K steps of labeled unbounded Petri nets are presented

    On the Enforcement of a Class of Nonlinear Constraints on Petri Nets

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    International audienceThis paper focuses on the enforcement of nonlinear constraints in Petri nets. First, a supervisory structure is proposed for a nonlinear constraint. The proposed structure consists of added places and transitions. It controls the transitions in the net to be controlled only but does not change its states since there is no arc between the added transitions and the places in the original net. Second, an integer linear programming model is proposed to transform a nonlinear constraint to a minimal number of conjunc-tive linear constraints that have the same control performance as the nonlinear one. By using a place invariant based method, the obtained linear constraints can be easily enforced by a set of control places. The control places consist to a supervisor that can enforce the given nonlinear constraint. On condition that the admissible markings space of a nonlinear constraint is non-convex, another integer linear programming model is developed to obtain a minimal number of constraints whose disjunctions are equivalent to the nonlinear constraint. Finally, a number of examples are provided to demonstrate the proposed approach

    On detectability of labeled Petri nets and finite automata

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    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 implies that there exists an infinite observed output sequence of the system such that each prefix of the output sequence with length greater than a given value allows an observer to determine if the current state belongs to a given set. We prove that the problem of verifying this property is undecidable for labeled Petri nets, and PSPACE-complete for finite automata. We also consider one new concept called eventual strong detectability. The new property implies that for each possible infinite observed output sequence, there exists a value such that each prefix of the output sequence with length greater than that value allows reconstructing the current state. We prove that for labeled Petri nets, the problem of verifying eventual strong detectability is decidable and EXPSPACE-hard, where the decidability result holds under a mild promptness assumption. For finite automata, we give a polynomial-time verification algorithm for the property. In addition, we prove that strong detectability is strictly stronger than eventual strong detectability for labeled Petri nets and even for deterministic finite automata

    Petri net controllers for Generalized Mutual Exclusion Constraints with floor operators

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    In this paper a special type of nonlinear marking specifications called stair generalized mutual exclusion constraints (stair-GMECs) is defined. A stair-GMEC can be represented by an inequality whose left-hand is a linear combination of floor functions. Stair-GMECs have higher modeling power than classical GMECs and can model legal marking sets that cannot be defined by OR–AND GMECs. We propose two algorithms to enforce a stair-GMEC as a closed-loop net, in which the control structure is composed by a residue counter, remainder counters, and duplicate transitions. We also show that the proposed control structure is maximally permissive since it prevents all and only the illegal trajectories of a plant net. This approach can be applied to both bounded and unbounded nets. Several examples are proposed to illustrate the approach

    A Polynomial Approach to Verifying the Existence of a Threatening Sensor Attacker

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    The development of cyber-physical systems (CPS) has brought much attention of researchers to cyber-attack and cyber-security. A sensor attacker targeting on a supervised discrete event system can modify a set of sensor readings and cause the closed-loop system to reach undesirable states. In this letter, we propose a new attack detection mechanism under which the supervisor only needs to keep track of the last observable event received. Given a plant and a supervisor enforcing a state specification, we define a sensor attacker threatening if it may cause the closed-loop system to enter a forbidden state. Our goal is to verify whether there exists such a threatening sensor attacker for a given controlled system. A new structure, called All Sensor Attack (ASA), is proposed to capture all possible sensor attacks launched by the attacker. Based on the ASA automaton, a necessary and sufficient condition for the existence of a stealthy threatening sensor attacker is presented. Finally, we show that the condition can be verified in polynomial time

    Detection and Prevention of Cyber-Attacks in Networked Control Systems

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    This paper addresses the problem of detection and prevention of cyber attacks in discrete event systems where the supervisor communicates with the plant via network channels. Random control delays may occur in such networked systems, hence the control of the supervisor could be affected. Furthermore, there is an attacker targeting the vulnerable actuators. The attacker can corrupt the control input generated by the supervisor, and aims at driving the plant to unsafe states. We propose a new approach to model the closed-loop system subject to control delays and attacks. The notion of AE-safe controllability in the networked control system is defined: it describes the ability to prevent the plant from reaching unsafe states after attacks are detected. A method for testing AE-safe controllability is also presented. Copyright (C) 2020 The Authors

    Firing rate optimization of cyclic timed event graphs by token allocations

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    In this paper, we deal with the problem of allocating a given number of tokens in a cyclic timed event graph (CTEG) so as to maximize the firing rate of the net. We propose three different approaches. The first one is a "greedy" incremental procedure that is computationally very efficient. The only drawback is that the convergence to the optimum is guaranteed only when the set of places where tokens can be allocated satisfies given constraints. The other two procedures involve the solution of a mixed integer linear programming problem. The first one needs the knowledge of the elementary circuits, thus it is convenient only for those classes of CTEG whose number of elementary circuits is roughly equal to the number of places, such as some kanban-systems. On the contrary, the second one enables one to overcome this difficulty, thus providing an efficient tool for the solution of allocation problems in complex manufacturing systems like job-shop systems

    Optimization of deterministic timed weighted marked graphs

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    Timed marked graphs, a special class of Petri nets, are extensively used to model and analyze cyclic manufacturing systems. Weighted marked graphs are convenient to model systems with bulk services and arrivals. We consider two problems of practical importance for this class of nets. The marking optimization problem consists in finding an initial marking to minimize the weighted sum of tokens in places, while the average cycle time is less than or equal to a given value. The cycle time optimization problem consists in finding an initial marking to minimize the average cycle time, while the weighted sum of tokens in places is less than or equal to a given value. We propose two heuristic algorithms to solve these problems. Several simulation studies show that the proposed approach is significantly more efficient than existing ones

    Dynamic max-consensus with local self-tuning

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    This work describes a novel control protocol for multi-agent systems to solve the dynamic max-consensus problem. In this problem, each agent has access to an external timevarying scalar signal and has the objective to estimate and track the maximum among all these signals by exploiting only local communications. The main strength of the proposed protocol is that it is able to self-tune its internal parameters in order to achieve an arbitrary small steady-state error without significantly affecting the convergence time. We employ the proposed protocol in the context of distributed graph parameter estimations, such as size, diameter, and radius, and provide simulations in the scenario of open multi-agent systems. Copyright (C) 2022 The Authors
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