This paper addresses the design of a gain-scheduled consensus protocol for multi-agent systems (MASs). Unlike conventional approaches that restrict the graph Laplacian to be fixed or switching matrices representing distinct topologies, we propose allowing it to vary as a function of a time-varying parameter vector available in real-time. For this situation, we derive design conditions that ensure convergence of the synchronization errors to zero in the form of a linear matrix inequality (LMI)-based feasibility problem, which can be efficiently solved using available tools. We illustrate the flexibility offered by a parameter-varying graph Laplacian formulation through two numerical examples that show the ability of the corresponding gain-scheduled consensus protocol to modulate various collective behaviors.
{"title":"Gain-Scheduled Consensus of Multi-Agent Systems Over Graphs Described by Parameter-Varying Laplacians","authors":"Damiano Rotondo;Didier Theilliol;Jean-Christophe Ponsart","doi":"10.1109/LCSYS.2025.3547864","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3547864","url":null,"abstract":"This paper addresses the design of a gain-scheduled consensus protocol for multi-agent systems (MASs). Unlike conventional approaches that restrict the graph Laplacian to be fixed or switching matrices representing distinct topologies, we propose allowing it to vary as a function of a time-varying parameter vector available in real-time. For this situation, we derive design conditions that ensure convergence of the synchronization errors to zero in the form of a linear matrix inequality (LMI)-based feasibility problem, which can be efficiently solved using available tools. We illustrate the flexibility offered by a parameter-varying graph Laplacian formulation through two numerical examples that show the ability of the corresponding gain-scheduled consensus protocol to modulate various collective behaviors.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3482-3487"},"PeriodicalIF":2.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-03DOI: 10.1109/LCSYS.2025.3547297
Burak Boyacıoğlu;Floris van Breugel
Given a set of measurements, observability characterizes the distinguishability of a system’s initial state, whereas constructability focuses on the final state in a trajectory. In the presence of process and/or measurement noise, the Fisher information matrices with respect to the initial and final states—equivalent to the stochastic observability and constructability Gramians—bound the performance of corresponding estimators through the Cramér-Rao inequality. This letter establishes a connection between stochastic observability and constructability of discrete-time linear systems and provides a more numerically robust way for calculating the stochastic observability Gramian. We define a dual system and show that the dual system’s stochastic constructability is equivalent to the original system’s stochastic observability, and vice versa. This duality enables the interchange of theorems and tools for observability and constructability. For example, we use this result to translate an existing recursive formula for the stochastic constructability Gramian into a formula for recursively calculating the stochastic observability Gramian for both time-varying and time-invariant systems, where this sequence converges for the latter. Finally, we illustrate the robustness of our formula compared to existing (non-recursive) formulas through a numerical example.
{"title":"Duality of Stochastic Observability and Constructability and Links to Fisher Information","authors":"Burak Boyacıoğlu;Floris van Breugel","doi":"10.1109/LCSYS.2025.3547297","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3547297","url":null,"abstract":"Given a set of measurements, observability characterizes the distinguishability of a system’s initial state, whereas constructability focuses on the final state in a trajectory. In the presence of process and/or measurement noise, the Fisher information matrices with respect to the initial and final states—equivalent to the stochastic observability and constructability Gramians—bound the performance of corresponding estimators through the Cramér-Rao inequality. This letter establishes a connection between stochastic observability and constructability of discrete-time linear systems and provides a more numerically robust way for calculating the stochastic observability Gramian. We define a dual system and show that the dual system’s stochastic constructability is equivalent to the original system’s stochastic observability, and vice versa. This duality enables the interchange of theorems and tools for observability and constructability. For example, we use this result to translate an existing recursive formula for the stochastic constructability Gramian into a formula for recursively calculating the stochastic observability Gramian for both time-varying and time-invariant systems, where this sequence converges for the latter. Finally, we illustrate the robustness of our formula compared to existing (non-recursive) formulas through a numerical example.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3458-3463"},"PeriodicalIF":2.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-03DOI: 10.1109/LCSYS.2025.3546990
Patrick Schmidt;Pavel Osinenko;Stefan Streif
This letter studies robustness to system disturbance and measurement noise of some popular general practical stabilization techniques, namely, Dini aiming, optimization-based cntrol and inf-convolution stabilization. Common to all these techniques is the explicit usage of a (general nonsmooth) control Lyapunov function, thus allowing to see them as a kind of generalization to the celebrated Sontag’s formula. It turns out that certain details of the above described robustness properties have not yet received the attention in literature they deserved. We provide new remarks, formalized in mathematical propositions, on robustness of selected popular stabilization techniques along with an extensive statistical case study on a robot parking problem.
{"title":"Some Remarks on Robustness of Sample-and-Hold Stabilization","authors":"Patrick Schmidt;Pavel Osinenko;Stefan Streif","doi":"10.1109/LCSYS.2025.3546990","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3546990","url":null,"abstract":"This letter studies robustness to system disturbance and measurement noise of some popular general practical stabilization techniques, namely, Dini aiming, optimization-based cntrol and inf-convolution stabilization. Common to all these techniques is the explicit usage of a (general nonsmooth) control Lyapunov function, thus allowing to see them as a kind of generalization to the celebrated Sontag’s formula. It turns out that certain details of the above described robustness properties have not yet received the attention in literature they deserved. We provide new remarks, formalized in mathematical propositions, on robustness of selected popular stabilization techniques along with an extensive statistical case study on a robot parking problem.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3464-3469"},"PeriodicalIF":2.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-03DOI: 10.1109/LCSYS.2025.3547687
Amin Kashiri;Yasin Yazıcıoğlu
We consider a coverage control problem, where a team of robots move in a convex domain to minimize a standard coverage cost. One prevalent approach to solve this problem is to use a gradient based controller (e.g., Lloyd’s algorithm), which stabilizes the local minima of such a coverage cost function. However, to the best of our knowledge, there are no formal results on how suboptimal these local minima can be. In this letter, we first show the existence of arbitrarily bad local minima. We then prove that a local search based approximation algorithm, which was originally developed for other location optimization problems (k-means/medians), can be adapted to the coverage control problem to stabilize configurations with bounded suboptimality in a decentralized manner. We also support our theoretical results with experiments on robots.
{"title":"Multi-Robot Coverage Control With Bounded Suboptimality Guarantees","authors":"Amin Kashiri;Yasin Yazıcıoğlu","doi":"10.1109/LCSYS.2025.3547687","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3547687","url":null,"abstract":"We consider a coverage control problem, where a team of robots move in a convex domain to minimize a standard coverage cost. One prevalent approach to solve this problem is to use a gradient based controller (e.g., Lloyd’s algorithm), which stabilizes the local minima of such a coverage cost function. However, to the best of our knowledge, there are no formal results on how suboptimal these local minima can be. In this letter, we first show the existence of arbitrarily bad local minima. We then prove that a local search based approximation algorithm, which was originally developed for other location optimization problems (k-means/medians), can be adapted to the coverage control problem to stabilize configurations with bounded suboptimality in a decentralized manner. We also support our theoretical results with experiments on robots.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3476-3481"},"PeriodicalIF":2.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this letter, a proximal dynamical system with time-varying coefficients for fixed-time (FXT) convergence is proposed to deal with the equilibrium problems (EPs). Initially, considering the non-smooth problem in optimization, we introduced the proximal dynamical system with FXT convergence. Compared with the finite-time (FT) convergence method, the convergence time of our algorithm is independent of the initial state, which enhances the robustness and ensures a fast convergence of the optimization process. Building on this foundation, the FXT convergence of the proximal dynamical system with time-varying coefficients is further investigated to realize the flexible adjustment of parameters, aiming at accelerating the convergence speed, reducing the oscillations and the process is not affected by the initial state. Ultimately, the efficacy of the proposed methods is validated through numerical experimentation.
{"title":"Proximal Dynamic Method With Time-Varying Coefficients for Equilibrium Problems: Fixed-Time Convergence","authors":"Suhela Lushate;Shuxin Liu;Rukeya Tohti;Haijun Jiang;Abdujelil Abdurahman","doi":"10.1109/LCSYS.2025.3546267","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3546267","url":null,"abstract":"In this letter, a proximal dynamical system with time-varying coefficients for fixed-time (FXT) convergence is proposed to deal with the equilibrium problems (EPs). Initially, considering the non-smooth problem in optimization, we introduced the proximal dynamical system with FXT convergence. Compared with the finite-time (FT) convergence method, the convergence time of our algorithm is independent of the initial state, which enhances the robustness and ensures a fast convergence of the optimization process. Building on this foundation, the FXT convergence of the proximal dynamical system with time-varying coefficients is further investigated to realize the flexible adjustment of parameters, aiming at accelerating the convergence speed, reducing the oscillations and the process is not affected by the initial state. Ultimately, the efficacy of the proposed methods is validated through numerical experimentation.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3446-3451"},"PeriodicalIF":2.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-27DOI: 10.1109/LCSYS.2025.3546525
Manmohan Sharma;Harshavarthini Shanmugam
A prescribed-time formation control of second-order multi-agent systems with partial loss of effectiveness of actuator efficiency and bias is proposed in this letter. An adaptive law is proposed to estimate the loss of effectiveness. An estimate of bias is also proposed from the Lyapunov theory. Rigorous mathematical proof with the help of a Lyapunov function is given to show that the closed-loop system augmented with the adaptive law converges to a bounded set in the prescribed time. All the signals are shown to be bounded and convergent to this set. Simulation results are given to demonstrate the effectiveness of the proposed approach.
{"title":"Prescribed-Time Formation Control of Second-Order Multi-Agent Systems in Presence of Actuator Faults","authors":"Manmohan Sharma;Harshavarthini Shanmugam","doi":"10.1109/LCSYS.2025.3546525","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3546525","url":null,"abstract":"A prescribed-time formation control of second-order multi-agent systems with partial loss of effectiveness of actuator efficiency and bias is proposed in this letter. An adaptive law is proposed to estimate the loss of effectiveness. An estimate of bias is also proposed from the Lyapunov theory. Rigorous mathematical proof with the help of a Lyapunov function is given to show that the closed-loop system augmented with the adaptive law converges to a bounded set in the prescribed time. All the signals are shown to be bounded and convergent to this set. Simulation results are given to demonstrate the effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3440-3445"},"PeriodicalIF":2.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Transport systems on networks are crucial in various applications, but face a significant risk of being adversely affected by unforeseen circumstances such as disasters. The application of entropy-regularized optimal transport (OT) on graph structures has been investigated to enhance the robustness of transport on such networks. In this letter, we propose an imitation-regularized OT (I-OT) that mathematically incorporates prior knowledge into the robustness of OT. This method is expected to enhance interpretability by integrating human insights into robustness and to accelerate practical applications. Furthermore, we mathematically verify the robustness of I-OT and discuss how these robustness properties relate to real-world applications. The effectiveness of this method is validated through a logistics simulation using automotive parts data.
{"title":"Imitation-Regularized Optimal Transport on Networks: Provable Robustness and Application to Logistics Planning","authors":"Koshi Oishi;Yota Hashizume;Tomohiko Jimbo;Hirotaka Kaji;Kenji Kashima","doi":"10.1109/LCSYS.2025.3546804","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3546804","url":null,"abstract":"Transport systems on networks are crucial in various applications, but face a significant risk of being adversely affected by unforeseen circumstances such as disasters. The application of entropy-regularized optimal transport (OT) on graph structures has been investigated to enhance the robustness of transport on such networks. In this letter, we propose an imitation-regularized OT (I-OT) that mathematically incorporates prior knowledge into the robustness of OT. This method is expected to enhance interpretability by integrating human insights into robustness and to accelerate practical applications. Furthermore, we mathematically verify the robustness of I-OT and discuss how these robustness properties relate to real-world applications. The effectiveness of this method is validated through a logistics simulation using automotive parts data.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3470-3475"},"PeriodicalIF":2.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The existing observer-based fault estimation methods for dynamic systems rarely consider the internal stochastic parametric uncertainty, limiting the reliability in practical applications. This letter aims to design a reliability-guaranteed fault observer for systems with stochastic parametric uncertainty. The condition for the observer stability and performance robustness is first described by a stochastic linear matrix inequality (LMI). By introducing the structural reliability index and certain matrix inequality lemmas, the original stochastic LMI is transformed into a deterministic probabilistic LMI with a probabilistic parameter of the reliability index. The probabilistic parameter quantifies the likelihood of achieving fault estimation performance and can be intentionally given or optimized to design a reliable fault observer. Simulation results with Monte-Carlo verification demonstrate the capability of the designed fault observer to estimate the constant and slowly time-varying faults, outperforming conventional methods in reliability.
{"title":"Reliability-Guaranteed Fault Observer Design for Systems With Stochastic Parametric Uncertainty","authors":"Tengtuo Chen;Jianchun Zhang;Wenshuo Li;Xiang Yu;Yi Yang;Lei Guo","doi":"10.1109/LCSYS.2025.3545552","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3545552","url":null,"abstract":"The existing observer-based fault estimation methods for dynamic systems rarely consider the internal stochastic parametric uncertainty, limiting the reliability in practical applications. This letter aims to design a reliability-guaranteed fault observer for systems with stochastic parametric uncertainty. The condition for the observer stability and performance robustness is first described by a stochastic linear matrix inequality (LMI). By introducing the structural reliability index and certain matrix inequality lemmas, the original stochastic LMI is transformed into a deterministic probabilistic LMI with a probabilistic parameter of the reliability index. The probabilistic parameter quantifies the likelihood of achieving fault estimation performance and can be intentionally given or optimized to design a reliable fault observer. Simulation results with Monte-Carlo verification demonstrate the capability of the designed fault observer to estimate the constant and slowly time-varying faults, outperforming conventional methods in reliability.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3434-3439"},"PeriodicalIF":2.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143564152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This letter considers the backstepping design of dynamically extended observers, or dynamic observers for short, for systems described by heterodirectional hyperbolic partial differential equations based on a collocated boundary measurement. In contrast to classical Luenberger-type observers, which usually consist of a copy of the system dynamics with appropriate injections of the measurement error, the dynamic observer incorporates an additional dynamics. The latter is chosen so that the extended observer error dynamics admits homogenized transport velocities on the unit spatial interval. With the added flexibility of the dynamic observer, using backstepping, it is possible to obtain a desired stable extended observer error dynamics with arbitrary in-domain couplings. An example illustrates the new dynamic observer design.
{"title":"Backstepping Design of Dynamic Observers for Hyperbolic Systems","authors":"Nicole Gehring;Joachim Deutscher;Abdurrahman Irscheid","doi":"10.1109/LCSYS.2025.3543913","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3543913","url":null,"abstract":"This letter considers the backstepping design of dynamically extended observers, or dynamic observers for short, for systems described by heterodirectional hyperbolic partial differential equations based on a collocated boundary measurement. In contrast to classical Luenberger-type observers, which usually consist of a copy of the system dynamics with appropriate injections of the measurement error, the dynamic observer incorporates an additional dynamics. The latter is chosen so that the extended observer error dynamics admits homogenized transport velocities on the unit spatial interval. With the added flexibility of the dynamic observer, using backstepping, it is possible to obtain a desired stable extended observer error dynamics with arbitrary in-domain couplings. An example illustrates the new dynamic observer design.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3452-3457"},"PeriodicalIF":2.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10896700","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-17DOI: 10.1109/LCSYS.2025.3542684
Vatsal Kedia;Sneha Susan George;Debraj Chakraborty
In this letter, the problem of reducing the computational complexity of a recently developed data-driven predictive control scheme is considered. For this purpose, a randomized data compression technique is proposed, which makes the dimension of the decision variable independent of the recorded data size, thereby reducing the complexity of the online optimization problems in data-driven predictive control to that of classical model-based predictive control. The proposed method outperforms other competing complexity reduction schemes in benchmark tests, while guaranteeing similar control performance and stability properties.
{"title":"Fast Data-Driven Predictive Control for LTI Systems: A Randomized Approach","authors":"Vatsal Kedia;Sneha Susan George;Debraj Chakraborty","doi":"10.1109/LCSYS.2025.3542684","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3542684","url":null,"abstract":"In this letter, the problem of reducing the computational complexity of a recently developed data-driven predictive control scheme is considered. For this purpose, a randomized data compression technique is proposed, which makes the dimension of the decision variable independent of the recorded data size, thereby reducing the complexity of the online optimization problems in data-driven predictive control to that of classical model-based predictive control. The proposed method outperforms other competing complexity reduction schemes in benchmark tests, while guaranteeing similar control performance and stability properties.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3416-3421"},"PeriodicalIF":2.4,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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