arXiv subjects

Carla Seatzu

Publications and source records attributed to Carla Seatzu.

At least 19 recordsLinked to original sources

arXiv2026

Dynamic Scheduling for Flexible Manufacturing Systems Based on Multi-Agent Deep Reinforcement Learning and Petri Nets

This paper investigates dynamic scheduling for flexible manufacturing systems (FMSs) subject to dynamic events, such as new order arrivals, temporary order cancellations, and machine failures. Traditional methods often face significant challenges in achieving real-time responsiveness under such conditions. To address this issue, the scheduling problem is formulated as a Markov decision process (MDP) with timed Petri nets, where the future evolution of the system depends exclusively on the current marking and the subsequently executed transitions, independent of historical trajectories. The state space and action space of the MDP are constructed using the notion of basis reachability graph (a compact state space representation) of Petri nets to alleviate the state explosion problem, thereby accelerating model training convergence. Meanwhile, a hierarchical dense reward function is constructed by integrating stepwise guidance with terminal evaluation. Then, a multi-agent proximal policy optimization algorithm is employed for model training under the centralized training and decentralized execution paradigm to improve scheduling efficiency. Numerical experiments are conducted involving typical dynamic events, and the results demonstrate that the proposed method can effectively handle dynamic events and achieve superior scheduling performance compared with conventional approaches.

eess.SY↗

arXiv2025

[Draft] High-order estimation-based properties and high-order observers for labeled finite-state automata

In this paper, we consider labeled finite-state automata (LFSAs), extend some state estimation-based properties from a single agent to a finite ordered set of agents. We also extend the notion of observer to \emph{high-order observer} using our \emph{concurrent composition}. As a result, a general framework for characterizing high-order estimation-based properties is built, in which each agent infers its preceding agent's estimation via all agents in front. The high-order observer plays the role of a basic tool to verify such properties. In more detail, in our general framework, the system's structure is publicly known to all agents $A_1,\dots,A_n$; each agent $A_i$ has its own observable event set $E_i$, and additionally knows all its preceding agents' observable events but can only observe its own observable events. The intuitive meaning of our high-order observer is to characterize what agent $A_n$ knows about what $A_{n-1}$ knows about \dots what $A_2$ knows about $A_1$'s state estimate of the system. This general framework can be regarded as an automata representation of dynamic epistemic logic. Compared with the classical representation of dynamic epistemic logic based on fragments of logic, our representation has advantages in property verification and flexibly changing agents to enforce properties. As case studies, this general framework applies to basic properties such as current-state opacity, strong current-state opacity, regular-language-based opacity, critical observability, high-order opacity, etc. Special cases for which verification can be done more efficiently are also discussed.

cs.FL↗

arXiv2025

Non-interference analysis of bounded labeled Petri nets

This paper focuses on a fundamental problem on information security of bounded labeled Petri nets: non-interference analysis. As in hierarchical control, we assume that a system is observed by users at different levels, namely high-level users and low-level users. The output events produced by the firing of transitions are also partitioned into high-level output events and low-level output events. In general, high-level users can observe the occurrence of all the output events, while low-level users can only observe the occurrence of low-level output events. A system is said to be non-interferent if low-level users cannot infer the firing of transitions labeled with high-level output events by looking at low-level outputs. In this paper, we study a particular non-interference property, namely strong non-deterministic non-interference (SNNI), using a special automaton called SNNI Verifier, and propose a necessary and sufficient condition for SNNI.

cs.FL↗

arXiv2025

Probabilistic State Estimation of Timed Probabilistic Discrete Event Systems via Artificial Neural Networks [Draft Version]

This paper is about the state estimation of timed probabilistic discrete event systems. The main contribution is to propose general procedures for developing state estimation approaches based on artificial neural networks. It is assumed that no formal model of the system exists but a data set is available, which contains the history of the timed behaviour of the systems. This dataset will be exploited to develop a neural network model that uses both logical and temporal information gathered during the functioning of the system as inputs and provides the state probability vector as output. Two main approaches are successively proposed (i) state estimation of timed probabilistic discrete event systems over observations: in this case the state estimate is reconstructed at the occurrence of each new observation; (ii) state estimation of timed probabilistic discrete event systems over time: in this case the state estimate is reconstructed at each clock time increment. For each approach, the paper outlines the process of data preprocessing, model building and implementation. This paper not only proposes groundbreaking approaches but also opens the door to further exploitation of artificial neural networks for the benefit of discrete event systems.

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arXiv2024

State estimation of timed automata under partial observation [Draft version]

In this paper, we consider partially observable timed automata endowed with a single clock. A time interval is associated with each transition specifying at which clock values it may occur. In addition, a resetting condition associated to a transition specifies how the clock value is updated upon its occurrence. This work deals with the estimation of the current state given a timed observation, i.e., a succession of pairs of an observable event and the time instant at which the event has occurred. The problem of state reachability in the timed automaton is reduced to the reachability analysis of the associated zone automaton, which provides a purely discrete event description of the behaviour of the timed automaton. An algorithm is formulated to provide an offline approach for state estimation of a timed automaton based on the assumption that the clock is reset upon the occurrence of each observable transition.

cs.FL↗

arXiv2021

Joint State Estimation Under Attack of Discrete Event Systems

The problem of state estimation in the setting of partially-observed discrete event systems subject to cyber attacks is considered. An operator observes a plant through a natural projection that hides the occurrence of certain events. The objective of the operator is that of estimating the current state of the system. The observation is corrupted by an attacker which can tamper with the readings of a set of sensors thus inserting some fake events or erasing some observations. The aim of the attacker is that of altering the state estimation of the operator. An automaton, called joint estimator, is defined to describe the set of all possible attacks. In more details, an unbounded joint estimator is obtained by concurrent composition of two state observers, the attacker observer and the operator observer. The joint estimator shows, for each possible corrupted observation, the joint state estimation, i.e., the set of states consistent with the uncorrupted observation and the set of states consistent with the corrupted observation. Such a structure can be used to establish if an attack function is harmful w.r.t. a misleading relation. Our approach is also extended to the case in which the attacker may insert at most n events between two consecutive observations.

cs.CR↗

arXiv2021

Generalized Current-State Opacity With Dynamically Changing Secrets

Opacity, an information-flow property related to the privacy and security of a system, has been extensively studied in the context of discrete event systems. Although various notions of opacity have been proposed, in all cases the considered secret was constant. This work focuses on current-state opacity, considering a scenario where the secret changes dynamically with the system evolution. In other words, we propose the new notion of generalized current-state opacity (GCSO), which is with respect to a dynamic-secret model rather than a constant secret. Moreover, we provide a method to verify GCSO based on the construction of the GCSO-verifier. Finally, a practical example is given to illustrate the proposed notion and the method for its verification.

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arXiv2020

A framework for the analysis of supervised discrete event systems under attack

This paper focuses on the problem of cyber attacks for discrete event systems under supervisory control. In more detail, the goal of the supervisor, who has a partial observation of the system evolution, is that of preventing the system from reaching a set of unsafe states. An attacker may act in two different ways: he can corrupt the observation of the supervisor editing the sensor readings, and can enable events that are disabled by the supervisor. This is done with the aim of leading the plant to an unsafe state, and keeping the supervisor unaware of that before the unsafe state is reached. A special automaton, called attack structure is constructed as the parallel composition of two special structures. Such an automaton can be used by the attacker to select appropriate actions (if any) to reach the above goal, or equivalently by the supervisor, to validate its robustness with respect to such attacks.

eess.SY↗

arXiv2019

Tracking Control by the Newton-Raphson Method with Output Prediction and Controller Speedup

This paper presents a control technique for output tracking of reference signals in continuous-time dynamical systems. The technique is comprised of the following three elements: (i) output prediction which has to track the reference signal, (ii) a controller based on an integrator with variable gain, and (iii) a speedup of the control action for enhancing the tracker's accuracy and, in some cases, guaranteeing stability of the closed-loop system. The technique is suitable for linear and nonlinear systems, implementable by simple algorithms, can track reference points as well as time-dependent reference signals, and may have large, even global domains of attraction. The derived theoretical results include convergence of the tracking controller and error analysis, and are supported by illustrative simulation and laboratory experiments.

math.OC↗

arXiv2019

Verification of infinite-step and K-step opacity Using Petri Nets

This paper addresses the problem of infinite-step opacity and K-step opacity of discrete event systems modeled with Petri nets. A Petri net system is said to be infinite-step/K-step opaque if all its secret states remains opaque to an intruder for any instant within infinite/K steps. In other words, the intruder is never able to ascertain that the system used to be in a secrete state within infinite/K steps based on its observation of the systems evolution. Based on the notion of basis reachability and the twoway observer, an efficient approach to verify infinite-step opacity and K-step opacity is proposed.

eess.SY↗

arXiv2019

Verification of Detectability Using Petri Nets and Detector

Detectability describes the property of a system to uniquely determine, after a finite number of observations, the current and subsequent states. In this paper, to reduce the complexity of checking the detectability properties in the framework of bounded labeled Petri nets, we use a new tool, which is called detector, to verifying the strong detectability and periodically strong detectability. First, an approach, which is based on the reachable graph and its detector, is proposed. Then, we develop a novel approach which is based on the analysis of the detector of the basis reachability graph. Without computing the whole reachability space, and without building the observer, the proposed approaches are more efficient.

eess.SY↗

arXiv2019

Verification of Detectability in Petri Nets Using Verifier Nets

Detectability describes the property of a system whose current and the subsequent states can be uniquely determined after a finite number of observations. In this paper, we developed a novel approach to verifying strong detectability and periodically strong detectability of bounded labeled Petri nets. Our approach is based on the analysis of the basis reachability graph of a special Petri net, called Verifier Net, that is built from the Petri net model of the given system. Without computing the whole reachability space and without enumerating all the markings, the proposed approaches are more efficient.

eess.SY↗

arXiv2019

Verification of C-detectability Using Petri Nets

Detectability describes the property of an system whose current and the subsequent states can be uniquely determined after a finite number of observations. In this paper, we relax detectability to C-detectability that only requires a given set of crucial states can be distinguished from other states. Four types of C-detectability: strong C-detectability, weak C-detectability, periodically strong C-detectability, and periodically weak C-detectability are defined in the framework of labeled Petri nets, which have larger modeling power than finite automata. Moreover, based on the notion of basis markings, the approaches are developed to verify the four C-detectability of a bounded labeled Petri net system. Without computing the whole reachability space and without enumerating all the markings consistent with an observation, the proposed approaches are more efficient.

eess.SY↗

arXiv2019

Tracking Control by the Newton-Raphson Flow: Applications to Autonomous Vehicles

This paper concerns applications of a recently-developed output-tracking technique to trajectory control of autonomous vehicles. The technique is based on three principles: Newton-Raphson flow for solving algebraic equations,output prediction, and controller speedup. Early applications of the technique, made to simple systems of an academic nature,were implemented by simple algorithms requiring modest computational efforts. In contrast, this paper tests it on commonly-used dynamic models to see if it can handle more complex control scenarios. Results are derived from simulations as well as a laboratory setting, and they indicate effective tracking convergence despite the simplicity of the control algorithm.

eess.SY↗

arXiv2016

Performance Regulation of Event-Driven Dynamical Systems Using Infinitesimal Perturbation Analysis

This paper presents a performance-regulation method for a class of stochastic timed event-driven systems aimed at output tracking of a given reference setpoint. The systems are either Discrete Event Dynamic Systems (DEDS) such as queueing networks or Petri nets, or Hybrid Systems (HS) with time-driven dynamics and event-driven dynamics, like fluid queues and hybrid Petri nets. The regulator, designed for simplicity and speed of computation, is comprised of a single integrator having a variable gain to ensure effective tracking under time-varying plants. The gain's computation is based on the Infinitesimal Perturbation Analysis (IPA) gradient of the plant function with respect to the control variable, and the resultant tracking can be quite robust with respect to modeling inaccuracies and gradient-estimation errors. The proposed technique is tested on examples taken from various application areas and modeled with different formalisms, including queueing models, Petri-net model of a production-inventory control system, and a stochastic DEDS model of a multicore chip control. Simulation results are presented in support of the proposed approach.

math.OC↗

arXiv2015

Congestion management in traffic-light intersections via Infinitesimal Perturbation Analysis

We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengths to given reference setpoints. The technique is based on multivariable integrators with adaptive gains, computed at each control cycle by assessing the IPA gradients of the plant functions. Moreover, the IPA gradients are computable on-line despite the absence of detailed models of the traffic flows. The technique is applied to a two-intersection system where it exhibits robustness with respect to modeling uncertainties and computing errors, thereby permitting us to simplify the on-line computations perhaps at the expense of accuracy while achieving the desired tracking. We compare, by simulation, the performance of a centralized, joint two-intersection control with distributed control of each intersection separately, and show similar performance of the two control schemes for a range of parameters.

math.OC↗

arXiv2015

Consensus on the average in arbitrary directed network topologies with time-delays

In this preliminary paper we study the stability property of a consensus on the average algorithm in arbitrary directed graphs with respect to communication/sensing time-delays. The proposed algorithm adds a storage variable to the agents' states so that the information about the average of the states is preserved despite the algorithm iterations are performed in an arbitrary strongly connected directed graph. We prove that for any network topology and choice of design parameters the consensus on the average algorithm is stable for sufficiently small delays. We provide simulations and numerical results to estimate the maximum delay allowed by an arbitrary unbalanced directed network topology.

math.OC↗

arXiv2014

Consensus in multi-agent systems with non-periodic sampled-data exchange and uncertain network topology

In this paper consensus in second-order multi-agent systems with a non-periodic sampled-data exchange among agents is investigated. The sampling is random with bounded inter-sampling intervals. It is assumed that each agent has exact knowledge of its own state at any time instant. The considered local interaction rule is PD-type. Sufficient conditions for stability of the consensus protocol to a time-invariant value are derived based on LMIs. Such conditions only require the knowledge of the connectivity of the graph modeling the network topology. Numerical simulations are presented to corroborate the theoretical results.

eess.SY↗