Automatica最新文献_第10页

Verification of current-state opacity and opaque time for labeled time Petri net systems 标记时间Petri网系统当前状态不透明和不透明时间的验证

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-09 DOI: 10.1016/j.automatica.2025.112241

Yuting Wang , Liang Li , Zhiwu Li

{"title":"Verification of current-state opacity and opaque time for labeled time Petri net systems","authors":"Yuting Wang , Liang Li , Zhiwu Li","doi":"10.1016/j.automatica.2025.112241","DOIUrl":"10.1016/j.automatica.2025.112241","url":null,"abstract":"<div><div>This paper investigates the verification of current-state opacity and opaque time in timed discrete event systems modeled with labeled time Petri nets (LTPNs). First, we formally conceptualize current-state opacity and opaque time for LTPN systems. Based on the solution of a set of linear programming problems (LPPs) associated with the transitions-related timing constraints in the modified state class graph (MSCG) of an LTPN system, an approach is proposed to find all the state classes and logic transition sequences that the system may generate at a given time instant. By utilizing such state classes and logic transition sequences, a method for verifying the current-state opacity of an LTPN system is presented, avoiding an exhaustive enumeration of the state classes that are consistent with all the observable label sequences at the time instant. To further acquire the current-state opaque time of the LTPN system, we propose a method for calculating the length of opaque time based on the solution of LPPs that are associated with the paths in the MSCG. Particularly, an algorithm is reported to compute the opaque time of an LTPN system with respect to a given secret. Finally, a case study is provided to illustrate the proposed algorithms to determine the current-state opacity and opaque time for an LTPN system.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112241"},"PeriodicalIF":4.8,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Probabilistic reachable sets of stochastic nonlinear systems with contextual uncertainties 具有上下文不确定性的随机非线性系统的概率可达集

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-06 DOI: 10.1016/j.automatica.2025.112237

Xun Shen , Ye Wang , Kazumune Hashimoto , Yuhu Wu , Sebastien Gros

{"title":"Probabilistic reachable sets of stochastic nonlinear systems with contextual uncertainties","authors":"Xun Shen , Ye Wang , Kazumune Hashimoto , Yuhu Wu , Sebastien Gros","doi":"10.1016/j.automatica.2025.112237","DOIUrl":"10.1016/j.automatica.2025.112237","url":null,"abstract":"<div><div>Validating and controlling safety-critical systems in uncertain environments necessitates probabilistic reachable sets of future state evolutions. The existing methods of computing probabilistic reachable sets normally assume that stochastic uncertainties are independent of system states, inputs, and other environment variables. However, this assumption falls short in many real-world applications, where the probability distribution governing uncertainties depends on these variables, referred to as <em>contextual uncertainties</em>. This paper addresses the challenge of computing probabilistic reachable sets of stochastic nonlinear states with contextual uncertainties by seeking minimum-volume polynomial sublevel sets with contextual chance constraints. The formulated problem cannot be solved by the existing sample-based approximation method since the existing methods do not consider conditional probability densities. To address this, we propose a consistent sample approximation of the original problem by leveraging conditional density estimation and resampling. The obtained approximate problem is a tractable optimization problem. Additionally, we prove the proposed sample-based approximation’s almost uniform convergence, showing that it gives the optimal solution almost consistently with the original ones. Through a numerical example, we evaluate the effectiveness of the proposed method against existing approaches, highlighting its capability to significantly reduce the bias inherent in sample-based approximation without considering a conditional probability density.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112237"},"PeriodicalIF":4.8,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Maximizing the smallest eigenvalue of grounded Laplacian matrices via edge addition

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-06 DOI: 10.1016/j.automatica.2025.112238

Xinfeng Ru , Weiguo Xia , Ming Cao

{"title":"Maximizing the smallest eigenvalue of grounded Laplacian matrices via edge addition","authors":"Xinfeng Ru , Weiguo Xia , Ming Cao","doi":"10.1016/j.automatica.2025.112238","DOIUrl":"10.1016/j.automatica.2025.112238","url":null,"abstract":"<div><div>The smallest eigenvalue of the grounded Laplacian matrix holds pivotal significance across various practical scenarios, particularly in characterizing the convergence rate of leader–follower networks in multi-agent systems, with a larger smallest eigenvalue indicating a faster convergence rate. This paper focuses on maximizing the smallest eigenvalue of the grounded Laplacian matrix via adding edges for both undirected and directed networks. For undirected networks, under intuitive conditions, we prove that adding one edge between two vertices that correspond to the smallest and largest eigenvector components for the smallest eigenvalue will maximize the smallest eigenvalue of the grounded Laplacian matrix. In addition, the discussion is extended to the case of multiple edge addition, where a suboptimal algorithm is proposed to maximize the eigenvalue with a low time complexity. For directed networks, when fixing a vertex <span><math><mi>i</mi></math></span> and adding an edge pointing to it, choosing the vertex, if there is any, that has the smallest eigenvector component than that of <span><math><mi>i</mi></math></span> leads to the maximal increase of the smallest eigenvalue. We apply the derived results to the distributed neighbor selection for directed networks.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112238"},"PeriodicalIF":4.8,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Properties of immersions for systems with multiple limit sets with implications to learning Koopman embeddings 多极限集系统的浸没性质及其对库普曼嵌入学习的启示

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-05 DOI: 10.1016/j.automatica.2025.112226

Zexiang Liu , Necmiye Ozay , Eduardo D. Sontag

引用次数: 0

Generic diagonalizability, structural functional observability and output controllability 一般对角性、结构功能可观察性和输出可控性

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-03 DOI: 10.1016/j.automatica.2025.112232

Yuan Zhang , Tyrone Fernando , Mohamed Darouach

{"title":"Generic diagonalizability, structural functional observability and output controllability","authors":"Yuan Zhang , Tyrone Fernando , Mohamed Darouach","doi":"10.1016/j.automatica.2025.112232","DOIUrl":"10.1016/j.automatica.2025.112232","url":null,"abstract":"<div><div>This paper investigates the structural functional observability (SFO) and structural output controllability (SOC) of a class of systems and explores the associated minimal sensor and actuator placement problems. The verification of SOC and the corresponding sensor and actuator placement problems, i.e., the problems of determining the minimum number of outputs and inputs required to achieve SFO and SOC, respectively, are yet open for general systems. This motivates our focus on a large class of systems enabling polynomial-time solutions. In this line, we first define and characterize generically diagonalizable systems, referring to structured systems for which almost all realizations of the state matrices are diagonalizable. We then develop computationally efficient criteria for SFO and SOC within the context of generically diagonalizable systems. Our work expands the class of systems amenable to polynomial-time SOC verification. Thanks to the simplicity of the obtained criteria, we derive closed-form solutions for determining the minimal sensor placement to achieve SFO and the minimal actuator deployment to achieve SOC in such systems, along with efficient weighted maximum matching-based and weighted maximum flow-based algorithms. For more general systems to achieve SFO, we establish an upper bound on the number of required sensors by identifying a non-decreasing property of SFO with respect to a specific class of edge additions, which is proven to be optimal under certain conditions.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112232"},"PeriodicalIF":4.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust fault detection method based on interval neural networks optimized by ellipsoid bundles

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-03 DOI: 10.1016/j.automatica.2025.112233

Meng Zhou , Yinyue Zhang , Jing Wang , Tarek Raïssi , Vicenç Puig

{"title":"Robust fault detection method based on interval neural networks optimized by ellipsoid bundles","authors":"Meng Zhou , Yinyue Zhang , Jing Wang , Tarek Raïssi , Vicenç Puig","doi":"10.1016/j.automatica.2025.112233","DOIUrl":"10.1016/j.automatica.2025.112233","url":null,"abstract":"<div><div>In this paper, a novel framework for interval prediction neural network model optimized by ellipsoid bundles is designed for data-driven systems with unknown but bounded noise and disturbances. Firstly, a point prediction neural network model is constructed with input and output data, the prediction error is assumed to be unknown but bounded. Then, a feasible set related to the output weights of the neural network model is described by ellipsoid bundles, which allows decreasing conservatism compared to other types of sets such as zonotopes or ellipsoids. To obtain a more precise description shape of the feasible set, an optimal iterative formula is theoretically derived by minimizing the Frobenius norm of ellipsoid bundles. Next, an outer bounding box is established to obtain the maximum and minimum weights that satisfy the feasible set, thereby providing the output prediction interval. This interval characterizes the systems’ disturbance and can be used as the threshold when dealing with fault diagnosis applications. Finally, the effectiveness of the proposed interval neural network model is demonstrated by using faulty data from a wastewater treatment process. Simulation results verify that the proposed method can achieve accurate prediction outputs and fault diagnosis performance.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112233"},"PeriodicalIF":4.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-triggered learning-based control for output tracking with unknown cost functions

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-03-03 DOI: 10.1016/j.automatica.2025.112235

Jiliang Song , Dawei Shi , Shu-Xia Tang , Hao Yu , Yang Shi

{"title":"Event-triggered learning-based control for output tracking with unknown cost functions","authors":"Jiliang Song , Dawei Shi , Shu-Xia Tang , Hao Yu , Yang Shi","doi":"10.1016/j.automatica.2025.112235","DOIUrl":"10.1016/j.automatica.2025.112235","url":null,"abstract":"<div><div>In this paper, a two-layer event-triggered learning-based control framework is proposed to address extremum seeking problem in networked control systems with limited communication resources and unknown cost function. In this framework, the lower layer is an event-triggered controller to drive the output to track the given setpoints generated from the upper layer, where a learning-based optimizer is developed to approach the extremum of the unknown cost function. Specifically, in the lower layer, an event-triggered output controller, based on a high-gain extended state observer, is designed to tackle uncertainties and disturbances. In the upper layer, a nonparametric gradient model is established, and then the gradient descent method is applied to generate setpoints for the tracking control. The update of the learning and optimization process is determined by the tracking performance of the lower layer. The stability and Zeno-freeness of the proposed event-triggered controller is proved. Furthermore, the dependence of the convergence rate of the proposed learning-based extremum seeking algorithm on the designed parameters is also explicitly characterized. Finally, the effectiveness of the proposed framework is validated by numerical examples.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112235"},"PeriodicalIF":4.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Emergent homeomorphic curves in swarms

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-02-28 DOI: 10.1016/j.automatica.2025.112221

Peter Travis Jardine, Sidney Givigi

引用次数: 0

Stochastically constrained best arm identification with Thompson sampling

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-02-28 DOI: 10.1016/j.automatica.2025.112223

Le Yang , Siyang Gao , Cheng Li , Yi Wang

引用次数: 0

Robust optimal density control of robotic swarms

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-02-28 DOI: 10.1016/j.automatica.2025.112218

Carlo Sinigaglia , Andrea Manzoni , Francesco Braghin , Spring Berman

{"title":"Robust optimal density control of robotic swarms","authors":"Carlo Sinigaglia , Andrea Manzoni , Francesco Braghin , Spring Berman","doi":"10.1016/j.automatica.2025.112218","DOIUrl":"10.1016/j.automatica.2025.112218","url":null,"abstract":"<div><div>In this paper we propose a computationally efficient, robust density control strategy for the mean-field model of a robotic swarm. We formulate a static optimal control problem (OCP) that computes a robot velocity field which drives the swarm to a target equilibrium density, and we prove the stability of the controlled system in the presence of transient perturbations and uncertainties in the initial conditions. The density dynamics are described by a linear elliptic advection–diffusion equation in which the control enters bilinearly into the advection term. The well-posedness of the state problem is ensured by an integral constraint. We prove the existence of optimal controls by embedding the state constraint into the weak formulation of the state dynamics. The resulting control field is space-dependent and does not require any communication between robots or costly density estimation algorithms. Based on the properties of the primal and dual systems, we first propose a method to accommodate the state constraint. Exploiting the properties of the state dynamics and associated controls, we then construct a modified dynamic OCP to speed up the convergence to the target equilibrium density of the associated static problem. We show that the finite-element discretization of the static and dynamic OCPs inherits the structure and several useful properties of their infinite-dimensional formulations. Finally, we demonstrate the effectiveness of our control approach through numerical simulations of scenarios with obstacles and an external velocity field.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"176 ","pages":"Article 112218"},"PeriodicalIF":4.8,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0