Automatica最新文献_第3页

On dissipativity of cross-entropy loss in training ResNets — A turnpike towards architecture search 训练ResNets中交叉熵损失的耗散性——结构搜索的收费公路

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.automatica.2025.112767

Jens Püttschneider , Timm Faulwasser

引用次数: 0

Constructing piecewise quadratic Lyapunov functions with linear programming for continuous-time switched and conewise linear systems 用线性规划构造连续时间切换线性系统的分段二次Lyapunov函数

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-01-15 DOI: 10.1016/j.automatica.2026.112838

Juan Javier Palacios Roman , Sigurdur Hafstein , Peter Giesl , Sebastiaan van den Eijnden , Stefania Andersen , W.P.M.H. Heemels

引用次数: 0

MAKO: Meta-Adaptive Koopman Operators for learning-based model predictive control of parametrically uncertain nonlinear systems 参数不确定非线性系统基于学习模型预测控制的元自适应Koopman算子

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-01-16 DOI: 10.1016/j.automatica.2026.112827

Minghao Han , Kiwan Wong , Adrian Wing-Keung Law , Xunyuan Yin

引用次数: 0

Input–output data-driven sensor selection for cyber-physical systems 网络物理系统的输入-输出数据驱动传感器选择

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-01-20 DOI: 10.1016/j.automatica.2026.112829

Filippos Fotiadis , Kyriakos G. Vamvoudakis

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引用次数: 0

Comments on “Innovative non-asymptotic and robust estimation method using auxiliary modulating dynamical systems” [Automatica 152 (2023) 110953] 关于“基于辅助调制动力系统的创新非渐近鲁棒估计方法”的评论[自动化]152 (2023)110953]

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-02-03 DOI: 10.1016/j.automatica.2026.112846

Matti Noack , Davi Goncalves Accioli , Johann Reger , Jerome Jouffroy

引用次数: 0

Differentially private projected gradient tracking for distributed constrained optimization 分布式约束优化的差分私有投影梯度跟踪

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-02-04 DOI: 10.1016/j.automatica.2026.112851

Zhen Yang , Wangli He , Guanrong Chen

引用次数: 0

The most powerful unfalsified linear parameter-varying model 最强大的非证伪线性参数变模型

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-02-02 DOI: 10.1016/j.automatica.2026.112855

Ivan Markovsky , Chris Verhoek , Roland Tóth

引用次数: 0

Quality evaluation-based resilient distributed state estimation over time-varying networks via multi-hop communication 基于质量评估的时变网络多跳通信弹性分布式状态估计

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.automatica.2026.112837

Rui Gao , Guang-Hong Yang , Tianyou Chai

{"title":"Quality evaluation-based resilient distributed state estimation over time-varying networks via multi-hop communication","authors":"Rui Gao , Guang-Hong Yang , Tianyou Chai","doi":"10.1016/j.automatica.2026.112837","DOIUrl":"10.1016/j.automatica.2026.112837","url":null,"abstract":"<div><div>This paper studies the problem of resilient distributed state estimation for a linear system using a set of agents connected through time-varying networks containing some Byzantine agents, where the Byzantine agents can arbitrarily manipulate the messages that they send or relay to other agents. First, an evaluation mechanism is introduced to assess the quality of the estimate generated by each agent at each step. Based on the quality evaluation and the multi-hop communication, a novel resilient distributed state estimation scheme is proposed, which enables each regular agent to evaluate the messages received from its time-varying multi-hop neighbors and discard the suspicious ones in real time. Then, to facilitate the stability analysis, the relationship between the estimates and the corresponding quality evaluations is established and the upper bound of the quality evaluations is derived. Specifically, the graph conditions under which all regular agents can estimate the state of the system exponentially fast at any given rate and even in finite time despite the existence of Byzantine agents are established. Different from the existing results requiring the time-varying networks to contain a sufficient amount of redundancy within bounded adjacent intervals, the proposed scheme can reduce the network redundancy requirement and allow the intervals over which such redundancy is preserved to grow over time. Finally, an example is simulated to validate the effectiveness of the proposed scheme.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"186 ","pages":"Article 112837"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014289","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

Two-player zero-sum hybrid games 二人零和混合游戏

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-03-01 Epub Date: 2025-12-15 DOI: 10.1016/j.automatica.2025.112688

Santiago J. Leudo, Ricardo G. Sanfelice

引用次数: 0

Data-driven certificate synthesis 数据驱动证书合成

IF 5.9 2区计算机科学

Automatica Pub Date : 2026-03-01 Epub Date: 2026-01-12 DOI: 10.1016/j.automatica.2025.112798

Luke Rickard , Alessandro Abate , Kostas Margellos

{"title":"Data-driven certificate synthesis","authors":"Luke Rickard , Alessandro Abate , Kostas Margellos","doi":"10.1016/j.automatica.2025.112798","DOIUrl":"10.1016/j.automatica.2025.112798","url":null,"abstract":"<div><div>We investigate the problem of verifying different properties of discrete time dynamical systems, namely, reachability, safety and reach-while-avoid. To achieve this, we adopt a data-driven perspective and, using past system trajectories as data, we aim at learning a specific function termed <em>certificate</em> for each property we wish to verify. We seek to minimize a loss function, designed to encompass conditions on the certificate to be learned that encode the satisfaction of the associated property. Besides learning a certificate, we quantify probabilistically its generalization properties, namely, how likely it is for a certificate to be valid (and hence for the associated property to be satisfied) when it comes to a new system trajectory not included in the training data set. We view this problem under the realm of probably approximately correct (PAC) learning under the notion of compression, and use recent advancements of the so-called scenario approach to obtain scalable generalization bounds on the learned certificates. To achieve this, we design a novel algorithm that minimizes the loss function and hence constructs a certificate, and at the same time determines a quantity termed compression, which is instrumental in obtaining meaningful probabilistic guarantees. This process is novel per se and provides a constructive mechanism for compression set calculation, thus opening the road for its use to more general non-convex optimization problems. We verify the efficacy of our methodology on several numerical case studies, and compare it (both theoretically and numerically) with closely related results on data-driven property verification.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"185 ","pages":"Article 112798"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978177","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