AutomaticaPub Date : 2025-06-07DOI: 10.1016/j.automatica.2025.112420
Dong Wang , Mingfei Chen , Jie Lian , Peng Lin , Zhengguang Wu
{"title":"Designing edge-based and node-based fully distributed algorithms for aggregative games with the adaptive technique","authors":"Dong Wang , Mingfei Chen , Jie Lian , Peng Lin , Zhengguang Wu","doi":"10.1016/j.automatica.2025.112420","DOIUrl":"10.1016/j.automatica.2025.112420","url":null,"abstract":"<div><div>This paper focuses on aggregative games with local feasibility decision sets in a partial-decision information scenario. To seek the Nash equilibrium in a fully distributed manner, adaptive algorithms with edge-based and node-based control gains are designed. In the edge-based adaptive algorithm, an auxiliary dynamics is developed with the consensus protocol and adaptively adjusts the edges’ weights. In the node-based adaptive algorithm, fully distributed decision-seeking is achieved by dynamically modifying the player’s weight based on the overall consensus error. By virtue of the designed adaptive parameters, players update decisions without any global information. Utilizing Lyapunov stability theory and the comparison lemma, the proposed algorithms converge exponentially to a small neighborhood of the Nash equilibrium. Furthermore, the proposed adaptive algorithms are extended to the prescribed-time case by combining the prescribed-time gain function and exponential adaptive parameters. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed algorithms.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112420"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229802","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}
AutomaticaPub Date : 2025-06-07DOI: 10.1016/j.automatica.2025.112296
Congcong Tian , Jie Mei , Kaixin Tian , Guangfu Ma
{"title":"Distributed adaptive Nash equilibrium seeking for games of heterogeneous high-order players over a directed graph","authors":"Congcong Tian , Jie Mei , Kaixin Tian , Guangfu Ma","doi":"10.1016/j.automatica.2025.112296","DOIUrl":"10.1016/j.automatica.2025.112296","url":null,"abstract":"<div><div>This paper investigates the distributed Nash equilibrium (NE) seeking problem for non-cooperative games involving heterogeneous high-order players over a directed graph. We first address the NE seeking problem of heterogeneous high-order integrators by employing a state transformation method, which reduces the high-order integrators to single integrators. A distributed NE seeking strategy is proposed, incorporating position estimators, gradient descent and state feedback. Furthermore, for the case of heterogeneous high-order players with parametric uncertainties, we propose another distributed strategy based on the model reference adaptive NE seeking idea, where a linear high-order virtual player is designed for each player to track. Both strategies converge to NE asymptotically, avoiding the need to interact with high-order derivative information or rely on shared gains. Finally, numerical simulations are performed to verify the effectiveness of the proposed algorithms.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112296"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229803","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}
AutomaticaPub Date : 2025-06-07DOI: 10.1016/j.automatica.2025.112409
Cesare Donati , Martina Mammarella , Fabrizio Dabbene , Carlo Novara , Constantino M. Lagoa
{"title":"Combining off-white and sparse black models in multi-step physics-based systems identification","authors":"Cesare Donati , Martina Mammarella , Fabrizio Dabbene , Carlo Novara , Constantino M. Lagoa","doi":"10.1016/j.automatica.2025.112409","DOIUrl":"10.1016/j.automatica.2025.112409","url":null,"abstract":"<div><div>In this paper, we propose a unified framework for identifying interpretable nonlinear dynamical models that preserve physical properties. The proposed approach integrates a model, based on physical principles, with black-box basis functions to compensate for unmodeled dynamics, thus ensuring accuracy over multi-step horizons. Additionally, we introduce penalty terms to enforce physical consistency and stability during training. We provide a comprehensive analysis of theoretical properties related to multi-step nonlinear system identification, establishing bounds on parameter estimation errors and conditions for sparsity recovery. The proposed framework demonstrates significant potential for improving model accuracy and reliability in various engineering applications, making a substantial step towards the effective use of combined off-white and sparse black models in system identification. The effectiveness of the proposed approach is proven on a nonlinear system identification benchmark.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112409"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229816","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}
{"title":"Evolution of measures in nonsmooth dynamical systems: Formalisms and computation","authors":"Saroj Prasad Chhatoi , Aneel Tanwani , Didier Henrion","doi":"10.1016/j.automatica.2025.112402","DOIUrl":"10.1016/j.automatica.2025.112402","url":null,"abstract":"<div><div>This article develops mathematical formalisms and provides numerical methods for studying the evolution of measures in nonsmooth dynamical systems using the continuity equation. The nonsmooth dynamical system is described by an evolution variational inequality and we derive the continuity equation associated with this system class using three different formalisms. The first formalism consists of using the superposition principle to describe the continuity equation for a measure that disintegrates into a probability measure supported on the set of vector fields and another measure representing the distribution of system trajectories at each time instant. The second formalism is based on the regularization of the nonsmooth vector field and describing the measure as the limit of a sequence of measures associated with the regularization parameter. In doing so, we obtain quantitative bounds on the Wasserstein metric between measure solutions of the regularized vector field and the limiting measure associated with the nonsmooth vector field. The third formalism uses a time-stepping algorithm to model a time-discretized evolution of the measures and show that the absolutely continuous trajectories associated with the continuity equation are recovered in the limit as the sampling time goes to zero. We also validate each formalism with numerical examples. For the first formalism, we use polynomial optimization techniques and the moment-SOS hierarchy to obtain approximate moments of the measures. For the second formalism, we illustrate the bounds on the Wasserstein metric for an academic example for which the closed-form expression of the Wasserstein metric can be calculated. For the third formalism, we illustrate the time-stepping based algorithm for measure evolution on an example that shows the effect of the concentration of measures.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112402"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229800","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}
AutomaticaPub Date : 2025-06-07DOI: 10.1016/j.automatica.2025.112400
Fabin Cheng, Jingang Lai
{"title":"Scale-free distributed control for the DC MG cluster under DoS attacks: An asynchronous switched strategy","authors":"Fabin Cheng, Jingang Lai","doi":"10.1016/j.automatica.2025.112400","DOIUrl":"10.1016/j.automatica.2025.112400","url":null,"abstract":"<div><div>This paper studies the voltage restoration problem of the DC Microgrid (MG) cluster with a two-layer communication structure under Denial-of-Service (DoS) attacks. Based on the open multiagent framework, an asynchronous switching strategy is designed to suppress the impact of DoS attacks on the entire MG cluster’s voltage restoration. Meanwhile, we derived the relationship between attack model parameters and communication link switching mode selection through the general model of DoS attacks and asynchronous switching methods based on average dwell time. Moreover, the designed distributed control protocol is scale-free; that is, it does not rely on any information from the two-layer communication structure and the number of distributed generations (DGs), which makes it universal. Through rigorous theoretical proof, it has been proven that in the DC MG cluster with two-layer communication structures, voltage restoration can be achieved regardless of the number and structure of DGs being attacked. Finally, two simulation examples on the MATLAB/SimPowerSystem, including a DC MG cluster consisting of 8 DGs and an IEEE 33-node system are used to investigate the scalability and flexibility of the proposed distributed control algorithm.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112400"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229801","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}
AutomaticaPub Date : 2025-06-07DOI: 10.1016/j.automatica.2025.112398
Prakitr Srisuma, George Barbastathis, Richard D. Braatz
{"title":"Simulation-based approach for fast optimal control of a Stefan problem with application to cell therapy","authors":"Prakitr Srisuma, George Barbastathis, Richard D. Braatz","doi":"10.1016/j.automatica.2025.112398","DOIUrl":"10.1016/j.automatica.2025.112398","url":null,"abstract":"<div><div>This article describes a new, efficient way of finding control and state trajectories in optimal control problems by reformulation as a system of differential–algebraic equations (DAEs). The optimal control and state vectors can be obtained via simulation of the resulting DAE system with the selected DAE solver, eliminating the need for an optimization solver. Our simulation-based approach is demonstrated and benchmarked against various optimization-based algorithms via four case studies associated with the optimization and control of a Stefan problem for cell therapy. The simulation-based approach is faster than every optimization-based method by more than an order of magnitude while giving similar/better accuracy in all cases. The solution obtained from the simulation-based approach is guaranteed to be optimal provided that at least one constraint or algebraic equation resulting from the reformulation remains active at all times. The proposed technique offers an efficient and reliable framework for optimal control, serving as a promising alternative to the traditional techniques in applications where speed is crucial, e.g., real-time online model predictive control.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112398"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229911","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}
AutomaticaPub Date : 2025-06-04DOI: 10.1016/j.automatica.2025.112399
Wenjie Liu , Lidong Li , Jian Sun , Fang Deng , Gang Wang , Jie Chen
{"title":"Data-driven control against false data injection attacks","authors":"Wenjie Liu , Lidong Li , Jian Sun , Fang Deng , Gang Wang , Jie Chen","doi":"10.1016/j.automatica.2025.112399","DOIUrl":"10.1016/j.automatica.2025.112399","url":null,"abstract":"<div><div>The rise of cyber-security concerns has brought significant attention to the analysis and design of cyber–physical systems (CPSs). Among the various types of cyberattacks, denial-of-service (DoS) attacks and false data injection (FDI) attacks can be easily launched and have become prominent threats. While resilient control against DoS attacks has received substantial research efforts, countermeasures developed against FDI attacks have been relatively limited, particularly when explicit system models are not available. To address this gap, the present paper focuses on the design of data-driven controllers for unknown linear systems subject to FDI attacks on the actuators, utilizing input-state data. To this end, a general FDI attack model is presented, which imposes minimally constraints on the switching frequency of attack channels and the magnitude of attack matrices. A dynamic state feedback control law is designed based on offline and online input-state data, which adapts to the channel switching of FDI attacks. This is achieved by solving two data-based semi-definite programs (SDPs) on-the-fly to yield a tight approximation of the set of subsystems consistent with both offline clean data and online attack-corrupted data. It is shown that under mild conditions on the attack, the proposed SDPs are recursively feasible and controller achieves exponential stability. Numerical examples showcase its effectiveness in mitigating the impact of FDI attacks.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112399"},"PeriodicalIF":4.8,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144203400","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}
AutomaticaPub Date : 2025-06-03DOI: 10.1016/j.automatica.2025.112388
Pascal den Boef, Jos Maubach, Wil Schilders, Nathan van de Wouw
{"title":"Stochastic optimization of large-scale parametrized dynamical systems","authors":"Pascal den Boef, Jos Maubach, Wil Schilders, Nathan van de Wouw","doi":"10.1016/j.automatica.2025.112388","DOIUrl":"10.1016/j.automatica.2025.112388","url":null,"abstract":"<div><div>Many problems in systems and control, such as controller synthesis and observer design, can be viewed as optimization problems involving dynamical systems: For instance, maximizing closed-loop performance in the controller synthesis setting. When the system includes large-scale, sparse state–space models, the optimization becomes computationally challenging. Existing methods in literature lack computational scalability or only solve an approximate version of the problem. We propose a method to locally minimize the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> norm of a differentiable parametrized dynamical system that resolves these issues. We do this by estimating the gradient of the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> norm using samples of the frequency response function, which can be obtained efficiently for large-scale, sparse state–space models. We prove that the scheme is guaranteed to preserve stability with high probability under boundedness conditions on the step size used in the optimization. We also obtain probabilistic guarantees that our method converges to a local minimizer. The method is applicable to problems involving non-realizable or infinite-dimensional dynamics. We demonstrate the effectiveness of the approach on two numerical examples.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112388"},"PeriodicalIF":4.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144203404","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}
AutomaticaPub Date : 2025-06-03DOI: 10.1016/j.automatica.2025.112389
Heeseung Bang, Andreas A. Malikopoulos
{"title":"Optimal trajectory planning meets network-level routing: Integrated control framework for emerging mobility systems","authors":"Heeseung Bang, Andreas A. Malikopoulos","doi":"10.1016/j.automatica.2025.112389","DOIUrl":"10.1016/j.automatica.2025.112389","url":null,"abstract":"<div><div>This paper introduces a hierarchical decision-making framework for emerging mobility systems that integrates network-level routing with vehicle-level coordination and control. We present an approach that combines flow-based routing for autonomous mobility-on-demand systems with energy-optimal trajectory planning for connected and automated vehicles (CAVs). Our method addresses the critical gap between macroscopic traffic flow optimization and microscopic vehicle control, ensuring that individually planned CAV trajectories collectively realize the system-optimal flow. For the trajectory planning problem, we propose an efficient method of utilizing analytical solutions to solve constrained optimization problems without computational burden. The proposed framework is demonstrated through numerical simulations in urban network scenarios with 100% CAV penetration. Our results illustrate the framework’s ability to generate and implement optimal traffic flows while satisfying safety constraints at the vehicle level.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112389"},"PeriodicalIF":4.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144203405","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}
AutomaticaPub Date : 2025-06-03DOI: 10.1016/j.automatica.2025.112395
Zaiwei Chen , Siva Theja Maguluri
{"title":"An approximate policy iteration viewpoint of actor–critic algorithms","authors":"Zaiwei Chen , Siva Theja Maguluri","doi":"10.1016/j.automatica.2025.112395","DOIUrl":"10.1016/j.automatica.2025.112395","url":null,"abstract":"<div><div>In this work, we establish sample complexity guarantees for a broad class of policy-space algorithms for reinforcement learning. A policy-space algorithm comprises an actor for policy improvement and a critic for policy evaluation. For the actor, we analyze update rules such as softmax, <span><math><mi>ϵ</mi></math></span>-greedy, and the celebrated natural policy gradient (NPG). Unlike traditional gradient-based analyses, we view NPG as an approximate policy iteration method. This perspective allows us to leverage the Bellman operator’s properties to show that NPG (without regularization) achieves geometric convergence to a globally optimal policy with increasing stepsizes. For the critic, we study TD-learning with linear function approximation and off-policy sampling. To address the instability of TD-learning in this setting, we propose a stable framework using multi-step returns and generalized importance sampling factors, including two specific algorithms: <span><math><mi>λ</mi></math></span>-averaged <span><math><mi>Q</mi></math></span>-trace and two-sided <span><math><mi>Q</mi></math></span>-trace. We also provide a finite-sample analysis for the critic. Combining the geometric convergence of the actor with the finite-sample results of the critic, we establish for the first time an overall sample complexity of <span><math><mrow><mover><mrow><mi>O</mi></mrow><mrow><mo>̃</mo></mrow></mover><mrow><mo>(</mo><msup><mrow><mi>ϵ</mi></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span> for finding an optimal policy (up to a function approximation error) using policy-space methods under off-policy sampling and linear function approximation.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112395"},"PeriodicalIF":4.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195767","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}