Pub Date : 2026-03-23DOI: 10.1016/j.automatica.2026.112931
Franco Angelo Torchiaro, Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola
{"title":"Distributed unknown input observers for linear time-invariant systems in discrete time","authors":"Franco Angelo Torchiaro, Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola","doi":"10.1016/j.automatica.2026.112931","DOIUrl":"https://doi.org/10.1016/j.automatica.2026.112931","url":null,"abstract":"","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"16 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147495624","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}
Pub Date : 2026-03-23DOI: 10.1016/j.automatica.2026.112926
Wouter Weekers, Alessandro Saccon, Nathan van de Wouw
{"title":"Data-efficient global extremum seeking framework for constrained optimization of nonlinear dynamical systems","authors":"Wouter Weekers, Alessandro Saccon, Nathan van de Wouw","doi":"10.1016/j.automatica.2026.112926","DOIUrl":"https://doi.org/10.1016/j.automatica.2026.112926","url":null,"abstract":"","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"16 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147495623","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}
Pub Date : 2026-03-19DOI: 10.1016/j.automatica.2026.112896
Boris Houska, Matthias A. Müller, Mario Eduardo Villanueva
{"title":"Control Lyapunov function design via configuration-constrained polyhedral computing","authors":"Boris Houska, Matthias A. Müller, Mario Eduardo Villanueva","doi":"10.1016/j.automatica.2026.112896","DOIUrl":"https://doi.org/10.1016/j.automatica.2026.112896","url":null,"abstract":"","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"7 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147495632","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}
Pub Date : 2026-03-01Epub Date: 2025-12-15DOI: 10.1016/j.automatica.2025.112688
Santiago J. Leudo, Ricardo G. Sanfelice
In this paper, we formulate a two-player zero-sum game under dynamic constraints defined by hybrid dynamical equations. The game consists of a min–max problem involving a cost functional that depends on the actions and resulting solutions to the hybrid system, defined as functions of hybrid time and, hence, can flow or jump. A conveniently defined terminal set allows us to recast both finite and infinite horizon problems. We present sufficient conditions given in terms of Hamilton–Jacobi–Bellman–Isaacs equations to guarantee that a solution to the game is attained. It is shown that when the players select the optimal strategy, the value function can be evaluated without computing solutions to the hybrid system. Under additional conditions, we show that the optimal state-feedback laws render a set asymptotically stable for the resulting hybrid closed-loop system. Applications of these games, presented here as robust control problems, include disturbance rejection and security problems.
{"title":"Two-player zero-sum hybrid games","authors":"Santiago J. Leudo, Ricardo G. Sanfelice","doi":"10.1016/j.automatica.2025.112688","DOIUrl":"10.1016/j.automatica.2025.112688","url":null,"abstract":"<div><div>In this paper, we formulate a two-player zero-sum game under dynamic constraints defined by hybrid dynamical equations. The game consists of a min–max problem involving a cost functional that depends on the actions and resulting solutions to the hybrid system, defined as functions of hybrid time and, hence, can flow or jump. A conveniently defined terminal set allows us to recast both finite and infinite horizon problems. We present sufficient conditions given in terms of Hamilton–Jacobi–Bellman–Isaacs equations to guarantee that a solution to the game is attained. It is shown that when the players select the optimal strategy, the value function can be evaluated without computing solutions to the hybrid system. Under additional conditions, we show that the optimal state-feedback laws render a set asymptotically stable for the resulting hybrid closed-loop system. Applications of these games, presented here as robust control problems, include disturbance rejection and security problems.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"185 ","pages":"Article 112688"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799658","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}
Pub Date : 2026-03-01Epub Date: 2026-01-12DOI: 10.1016/j.automatica.2025.112798
Luke Rickard , Alessandro Abate , Kostas Margellos
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 certificate 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.
{"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}
Pub Date : 2026-03-01Epub Date: 2026-01-02DOI: 10.1016/j.automatica.2025.112810
Bin Zhou
This paper addresses the problems of exact prescribed-time stabilization and observer design for a class of multi-input-multi-output (MIMO) nonlinear systems. By introducing the concept of left and right clustered matrices and exploring their properties, solutions to two classes of parametric Lyapunov equations (PLEs) associated with the coefficients of the linear part of the MIMO nonlinear systems are thoroughly investigated. These two PLEs are then utilized as the key tool to solve respectively the exact prescribed-time stabilization of the MIMO nonlinear system where the nonlinear functions satisfy a linear growth condition with unknown coefficients, and the exact prescribed-time observer design of the MIMO nonlinear system where the nonlinear functions are known and satisfy the Lipschitz condition. The approach is also extended to solve the problem of prescribed-time stabilization of a class of MIMO nonlinear systems by observer-based output feedback. Finally, two numerical examples demonstrate the effectiveness of the proposed approaches.
{"title":"Exact prescribed-time stabilization and observer design for a class of MIMO nonlinear systems","authors":"Bin Zhou","doi":"10.1016/j.automatica.2025.112810","DOIUrl":"10.1016/j.automatica.2025.112810","url":null,"abstract":"<div><div>This paper addresses the problems of exact prescribed-time stabilization and observer design for a class of multi-input-multi-output (MIMO) nonlinear systems. By introducing the concept of left and right clustered matrices and exploring their properties, solutions to two classes of parametric Lyapunov equations (PLEs) associated with the coefficients of the linear part of the MIMO nonlinear systems are thoroughly investigated. These two PLEs are then utilized as the key tool to solve respectively the exact prescribed-time stabilization of the MIMO nonlinear system where the nonlinear functions satisfy a linear growth condition with unknown coefficients, and the exact prescribed-time observer design of the MIMO nonlinear system where the nonlinear functions are known and satisfy the Lipschitz condition. The approach is also extended to solve the problem of prescribed-time stabilization of a class of MIMO nonlinear systems by observer-based output feedback. Finally, two numerical examples demonstrate the effectiveness of the proposed approaches.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"185 ","pages":"Article 112810"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884869","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}
Pub Date : 2026-03-01Epub Date: 2025-12-19DOI: 10.1016/j.automatica.2025.112787
Lapo Frascati , Alberto Bemporad
This paper proposes a novel combination of extended Kalman filtering (EKF) with the alternating direction method of multipliers (ADMM) for learning parametric nonlinear models online under non-smooth regularization terms, including and penalties and bound constraints on model parameters. For the case of linear time-varying models and non-smooth convex regularization terms, we provide a sublinear regret bound that ensures the proper behavior of the online learning strategy. The approach is computationally efficient for a wide range of regularization terms, which makes it appealing for its use in embedded control applications for online model adaptation. We show the performance of the proposed method in three simulation examples, highlighting its effectiveness compared to other batch and online algorithms.
{"title":"Online learning of nonlinear parametric models under non-smooth regularization using EKF and ADMM","authors":"Lapo Frascati , Alberto Bemporad","doi":"10.1016/j.automatica.2025.112787","DOIUrl":"10.1016/j.automatica.2025.112787","url":null,"abstract":"<div><div>This paper proposes a novel combination of extended Kalman filtering (EKF) with the alternating direction method of multipliers (ADMM) for learning parametric nonlinear models online under non-smooth regularization terms, including <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> penalties and bound constraints on model parameters. For the case of linear time-varying models and non-smooth convex regularization terms, we provide a sublinear regret bound that ensures the proper behavior of the online learning strategy. The approach is computationally efficient for a wide range of regularization terms, which makes it appealing for its use in embedded control applications for online model adaptation. We show the performance of the proposed method in three simulation examples, highlighting its effectiveness compared to other batch and online algorithms.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"185 ","pages":"Article 112787"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784442","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}
Pub Date : 2026-03-01Epub Date: 2025-12-17DOI: 10.1016/j.automatica.2025.112755
Zheng Ning , Shuangshuang Yu , Chao Ge , Ge Chen
Two-component chemical self-assembly has been a decisive method of creating various structures and is the basis of the superlattice in material science; however because the process of self-assembly is tangled and hard to describe, there is little theoretical research, and mathematical theory is particularly lacking currently. Based on some assumptions of the hard sphere model and Coulombic assembly experiment, this paper presents a novel multi-agent system for two-component chemical self-assembly using a group of stochastic differential equations. The existence and uniqueness theorem of the solution is also presented. A structure control problem is proposed by taking the bond-orientational order as the characteristic function of the assembled product structure, and the temperature as the control input. Our simulations show that the bond-orientational order of self-assembled product is heavily related to the final temperature, but has little relevance to the control path from the initial temperature to the final temperature.
{"title":"Two-component nanoparticle self-assembly: Modeling, analysis, and structure control","authors":"Zheng Ning , Shuangshuang Yu , Chao Ge , Ge Chen","doi":"10.1016/j.automatica.2025.112755","DOIUrl":"10.1016/j.automatica.2025.112755","url":null,"abstract":"<div><div>Two-component chemical self-assembly has been a decisive method of creating various structures and is the basis of the superlattice in material science; however because the process of self-assembly is tangled and hard to describe, there is little theoretical research, and mathematical theory is particularly lacking currently. Based on some assumptions of the hard sphere model and Coulombic assembly experiment, this paper presents a novel multi-agent system for two-component chemical self-assembly using a group of stochastic differential equations. The existence and uniqueness theorem of the solution is also presented. A structure control problem is proposed by taking the bond-orientational order as the characteristic function of the assembled product structure, and the temperature as the control input. Our simulations show that the bond-orientational order of self-assembled product is heavily related to the final temperature, but has little relevance to the control path from the initial temperature to the final temperature.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"185 ","pages":"Article 112755"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799190","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}
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