AutomaticaPub Date : 2025-02-01DOI: 10.1016/j.automatica.2024.112007
Jiaxu Liu , Song Chen
{"title":"Comments on “Distributed optimization of multi-integrator agent systems with mixed neighbor interactions” [Automatica 157 (2023) 111245 ]","authors":"Jiaxu Liu , Song Chen","doi":"10.1016/j.automatica.2024.112007","DOIUrl":"10.1016/j.automatica.2024.112007","url":null,"abstract":"<div><div>This note aims to identify and rectify the flaws found in the proof of Chen et al. (2023), specifically in Lemma 2, Lemma 3, Theorem 1, and Theorem 2. While the conclusions of Lemma 2, Lemma 3, and Theorem 1 remain valid, certain aspects of their proofs are found to be flawed. This note provides modifications to address these flaws. Additionally, the statement and proof of Theorem 2 are shown to be incorrect. A corrected Theorem 2 with proof is given.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112007"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095093","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 : 2025-02-01DOI: 10.1016/j.automatica.2024.112008
Zhao Chen, Xiaohong Nian, Qing Meng
{"title":"Authors’ Reply to ‘Comments on “Distributed optimization of multi-integrator agent systems with mixed neighbor interactions” [Automatica 157 (2023) 111245]’","authors":"Zhao Chen, Xiaohong Nian, Qing Meng","doi":"10.1016/j.automatica.2024.112008","DOIUrl":"10.1016/j.automatica.2024.112008","url":null,"abstract":"","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112008"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095096","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 : 2025-02-01DOI: 10.1016/j.automatica.2024.112017
Youdao Ma , Zhenhua Wang , Nacim Meslem , Tarek Raïssi
{"title":"Functional interval estimation for continuous-time linear systems with time-invariant uncertainties","authors":"Youdao Ma , Zhenhua Wang , Nacim Meslem , Tarek Raïssi","doi":"10.1016/j.automatica.2024.112017","DOIUrl":"10.1016/j.automatica.2024.112017","url":null,"abstract":"<div><div>This paper investigates functional interval estimation for continuous-time linear systems subject to both time-varying and time-invariant uncertainties. Two novel methods are proposed based on peak-to-peak functional observer design and interval analysis. First, we present a splitting-based method that splits the estimation error dynamics into two subsystems to handle the time-invariant disturbances and provide accurate estimation results. Then, to further enhance the estimation accuracy, we present an augmentation-based method that considers the time invariance in both functional observer design and reliable interval estimation. The relationship between a state-of-art method and the proposed methods are analysed theoretically. Finally, simulation results are provided to demonstrate the performances of the proposed methods.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112017"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095095","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 : 2025-02-01DOI: 10.1016/j.automatica.2024.112010
Ali Kashani, Claus Danielson
{"title":"Data-driven invariant set for nonlinear systems with application to command governors","authors":"Ali Kashani, Claus Danielson","doi":"10.1016/j.automatica.2024.112010","DOIUrl":"10.1016/j.automatica.2024.112010","url":null,"abstract":"<div><div>This paper presents a novel approach to synthesize positive invariant sets for unmodeled nonlinear systems using direct data-driven techniques. The data-driven invariant sets are used to design a data-driven command governor that selects a command for the closed-loop system to enforce constraints. Using basis functions, we solve a semi-definite program to learn a sum-of-squares Lyapunov-like function whose unity level-set is a constraint admissible positive invariant set, which determines the constraint admissible states and input commands. Leveraging Lipschitz properties of the system, we prove that tightening the model-based design ensures robustness of the invariant set to the inherent plant uncertainty in a data-driven framework. To mitigate the curse-of-dimensionality, we repose the semi-definite program into a linear program. We validate our approach through two examples: First, we present an illustrative example where we can analytically compute the maximum positive invariant set and compare with the presented data-driven invariant set. Second, we present a practical autonomous driving scenario to demonstrate the utility of the presented method for nonlinear systems.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112010"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095092","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 : 2025-02-01DOI: 10.1016/j.automatica.2024.111988
Jin Zhu , Zhi Xie , Geir E. Dullerud
{"title":"Event-triggered stabilization of uncertain switched linear systems under finite feedback bit rate","authors":"Jin Zhu , Zhi Xie , Geir E. Dullerud","doi":"10.1016/j.automatica.2024.111988","DOIUrl":"10.1016/j.automatica.2024.111988","url":null,"abstract":"<div><div>This paper investigates event-triggered stabilization of uncertain switched linear systems under finite feedback bit rate where the boundary of model uncertainty is unknown. Based on the appropriate boundary estimation, a novel communication and control strategy is given to obtain qualified feedback gains and visible system states in which the event-triggering mechanism is adopted. By utilizing the additional timing information carried by the triggering moments, the proposed event-triggering controller can achieve a lower occupation of average bit rate to ensure exponential convergence of the system state. Simulation results show the effectiveness of our method.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 111988"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095094","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":"Distributed optimal coverage control in multi-agent systems: Known and unknown environments","authors":"Mohammadhasan Faghihi, Meysam Yadegar, Mohammadhosein Bakhtiaridoust, Nader Meskin, Javad Sharifi, Peng Shi","doi":"10.1016/j.automatica.2024.112031","DOIUrl":"https://doi.org/10.1016/j.automatica.2024.112031","url":null,"abstract":"This paper introduces a novel approach to solve the coverage optimization problem in multi-agent systems. The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. Theoretical analyses are conducted to assure the asymptotic convergence of agents toward an optimal configuration. A distinguishing feature of this approach lies in its departure from the reliance on geometric methods that are characteristic of Voronoi-based approaches; hence it can be implemented more simply. Remarkably, the technique is adaptive and applicable to various environments with both known and unknown information distributions. Lastly, the efficacy of the proposed method is demonstrated through simulations, and the obtained results are compared with those of Voronoi-based algorithms.","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"13 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816496","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 : 2024-12-03DOI: 10.1016/j.automatica.2024.112005
Jun Zheng , Guchuan Zhu
{"title":"Generalized Lyapunov functionals for the input-to-state stability of infinite-dimensional systems","authors":"Jun Zheng , Guchuan Zhu","doi":"10.1016/j.automatica.2024.112005","DOIUrl":"10.1016/j.automatica.2024.112005","url":null,"abstract":"<div><div>This paper addresses the input-to-state stability (ISS) of infinite-dimensional systems by introducing a novel notion named <em>generalized ISS-Lyapunov functional</em> (GISS-LF) and the corresponding ISS Lyapunov theorem. Unlike the classical ISS-Lyapunov functional (ISS-LF) that must be positive definite, a GISS-LF can be positive semidefinite. Moreover, such a functional considers not only the relationship with elements in the state space but also takes into account the elements in the input space via a family of certain functionals. Consequently, this notion provides more options in constructing Lyapunov functionals for the ISS assessment of infinite-dimensional systems. In particular, we provide a positive answer to the open question raised by A. Mironchenko and C. Prieur, “Input-to-state stability of infinite-dimensional systems: recent results and open questions”, (Mironchenko and Prieur, 2020), regarding the existence of a coercive ISS-LF for the heat equation with Dirichlet boundary disturbances. To demonstrate the application of the proposed method, which we refer to as the generalized Lyapunov method, we present two examples, showing how to construct GISS-LFs by using positive semidefinite and non-coercive functionals for nonlinear parabolic equations defined over higher dimensional domains with Dirichlet boundary disturbances, and to derive small-gain conditions for guaranteeing the ISS with respect to distributed in-domain disturbances for coupled nonlinear degenerate parabolic equations, which contain ordinary differential equations as special cases.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112005"},"PeriodicalIF":4.8,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759491","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 : 2024-12-03DOI: 10.1016/j.automatica.2024.112009
Kai Zhang, Bin Zhou
{"title":"Fully distributed and attack-immune protocols for linear multiagent systems by linear time-varying feedback","authors":"Kai Zhang, Bin Zhou","doi":"10.1016/j.automatica.2024.112009","DOIUrl":"10.1016/j.automatica.2024.112009","url":null,"abstract":"<div><div>This paper addresses the leader-following consensus problem for general linear multiagent systems under general directed topology, with a focus on the scenarios where only relative output information is available. To solve such problem, most existing observer-based protocols rely on relative observer information among neighboring agents, which is obtained through the communication network and can be susceptible to network attacks. To overcome this limitation, this paper proposes a novel class of distributed observer-based linear time-varying protocols, in which the feedback gain is designed with two time-varying terms, one of which tends towards infinity as time increases, while the other tends towards zero. Compared to existing protocols, the proposed protocols offer significant advantages. Notably, they do not require information exchange through the communication network, making them immune to network attacks. Furthermore, the protocols operate in a fully distributed manner, which makes them resilient to changes in the topology graph. Simulation results demonstrate the effectiveness of the proposed approach.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112009"},"PeriodicalIF":4.8,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759728","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 : 2024-12-02DOI: 10.1016/j.automatica.2024.111999
Jiancheng Zhang , Yongduan Song , Gang Zheng
{"title":"Prescribed-time observer for descriptor systems with unknown input","authors":"Jiancheng Zhang , Yongduan Song , Gang Zheng","doi":"10.1016/j.automatica.2024.111999","DOIUrl":"10.1016/j.automatica.2024.111999","url":null,"abstract":"<div><div>This paper investigates the problem of simultaneous state and unknown input estimation/observation within a prescribed time for a class of descriptor systems with unknown inputs (UIs). Firstly, for the descriptor system with UIs, a new structure decomposition is developed which provides a more straightforward way to estimate the state and UIs. Subsequently, based on the sub-system obtained by the decomposition, new prescribed time unknown input observers (PTUIOs) are developed for both the single-output and the multiple-output cases, which, on the one hand, achieves the simultaneous state and UI estimation within an arbitrarily prescribed time, and on the other hand, breaks through the restriction imposed in the literature that the sub-system should be single-output and meanwhile be in a special canonical form. The necessary and sufficient conditions for the existence of the PTUIO are established in terms of the original system matrices. Finally, two examples are presented to verify the effectiveness of the proposed method.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 111999"},"PeriodicalIF":4.8,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759490","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":"Meta-learning for model-reference data-driven control","authors":"Riccardo Busetto , Valentina Breschi , Simone Formentin","doi":"10.1016/j.automatica.2024.112006","DOIUrl":"10.1016/j.automatica.2024.112006","url":null,"abstract":"<div><div>One-shot direct model-reference control design techniques, like the Virtual Reference Feedback Tuning (VRFT) approach, offer time-saving solutions for calibrating fixed-structure controllers. Nonetheless, such methods are known to be highly sensitive to the quality of data, often requiring long and costly experiments to attain acceptable closed-loop performance. These features might prevent the widespread adoption of such techniques, especially in low-data regimes. In this paper, we argue that the inherent similarity of many industrially relevant systems may come at hand, offering additional information from plants that are similar (yet not equal) to the system one aims to control. Assuming that this supplementary information is available, we propose a novel, direct design approach that leverages data from similar plants, the knowledge of controllers calibrated on them, and the corresponding closed-loop performance to enhance model-reference control design. By constructing the new controller as a combination of the available ones, our approach exploits all the available priors following a <em>meta-learning</em> philosophy, ensuring non-decreasing performance. An extensive numerical analysis supports our claims, highlighting the effectiveness of the proposed method in achieving performance comparable to iterative approaches, while retaining the efficiency of one-shot direct data-driven methods like VRFT.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"172 ","pages":"Article 112006"},"PeriodicalIF":4.8,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759488","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}