{"title":"Erratum to “On Regular Regressors in Adaptive Control”","authors":"Erick Mejia Uzeda;Mireille E. Broucke","doi":"10.1109/LCSYS.2025.3579901","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3579901","url":null,"abstract":"Presents corrections to the paper, (Erratum to “On Regular Regressors in Adaptive Control”).","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1459-1459"},"PeriodicalIF":2.4,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11080393","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634779","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}
{"title":"On the Uniqueness of Solution to the Inverse Optimal Control Problem for the Hard-Constrained Minimum Principle-Based Method","authors":"Afreen Islam;Guido Herrmann;Joaquin Carrasco","doi":"10.1109/LCSYS.2025.3586916","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586916","url":null,"abstract":"In this letter, the hard-constrained minimum principle based method for solving the inverse optimal control (IOC) problem has been considered. Specifically, this letter investigates the kinds of closed-loop system trajectories, initial conditions and system dynamics for which a unique solution to the IOC problem can be obtained for this method. For this purpose, a matrix associated with the optimization problem involved in this IOC approach is tested for full rankness. It was found that for this method, in addition to initial conditions and types of closed-loop system trajectories, the open-loop system dynamics has an important role in determining if a unique solution to the IOC problem can be obtained. Rigorous mathematical and numerical analysis for different types of trajectories, initial conditions and system dynamics have been presented.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1856-1861"},"PeriodicalIF":2.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687657","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}
{"title":"Leaky-Integrator Echo State Network Incremental ISS Stability Analysis","authors":"Hao Deng;Cristina Stoica;Mohammed Chadli","doi":"10.1109/LCSYS.2025.3587362","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3587362","url":null,"abstract":"This letter proposes a novel incremental input-to-state stability condition for a discrete-time leaky-integrator echo state network. The derived condition is further utilized for control design through Linear Matrix Inequalities (LMIs). The corresponding observer design LMI condition is also derived. A numerical simulation showcases the effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1814-1819"},"PeriodicalIF":2.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687669","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}
{"title":"Priority-Driven Constraints Softening in Safe MPC for Perturbed Systems","authors":"Ying Shuai Quan;Mohammad Jeddi;Francesco Prignoli;Paolo Falcone","doi":"10.1109/LCSYS.2025.3580494","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3580494","url":null,"abstract":"This letter presents a safe model predictive control framework designed to guarantee the satisfaction of hard safety constraints, for perturbed dynamical systems. Safety is guaranteed by softening the constraints selected on a priority basis from a subset of constraints defined by the designer. Since such an online selection is the result of an auxiliary optimization problem, its computational overhead is alleviated by off-line learning its approximated solution, rather than solving it exactly online. Simulation results, obtained from an automated driving application, show that the proposed approach provides guarantees of collision-avoidance hard constraints despite the unpredicted behaviors of the surrounding environment.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1069-1074"},"PeriodicalIF":2.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072918","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589369","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}
{"title":"Leader-Centric Time-Varying Formation Tracking Control for Multi-Agent Systems via Event-Triggered Mechanism","authors":"Ankush Thakur;Ravi Kiran Akumalla;Tushar Jain","doi":"10.1109/LCSYS.2025.3586853","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586853","url":null,"abstract":"This letter introduces a novel event-triggered control design methodology for achieving leader-centric time-varying formation tracking (LCTVFT) in linear multi-agent systems (MASs) subject to actuator bias faults. Within this framework, the leader dynamically determines the desired formation for the followers, which is unknown to them a priori. Achieving formation tracking, despite actuator bias faults and unpredictable leader maneuvering, strictly requires the followers to continuously infer the leader’s decisions and take control actions, posing significant implementation challenges. To address this issue, a fixed-time event-triggered formation observer (ETFO) is proposed to estimate the leader’s information through event-triggered updates, thereby enabling responsive formation tracking. The fixed-time stability of the overall closed-loop system is rigorously established over every subinterval of leader-assigned formations using Lyapunov stability analysis. A simulation example is provided to validate the effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1844-1849"},"PeriodicalIF":2.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712084","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}
{"title":"Periodic Disturbance Learning Model Predictive Control","authors":"Syed Hassan Ahmed;Tommaso Bonetti;Lorenzo Fagiano","doi":"10.1109/LCSYS.2025.3586633","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586633","url":null,"abstract":"A novel Model Predictive Control (MPC) framework called disturbance-learning MPC (DL-MPC) for constrained LTI systems subject to bounded disturbances is proposed. The primary objective is to improve the disturbance rejection performance of the tube-based MPC (tube-MPC) law, especially focusing on periodic disturbance signals. Based on convex optimization, the method uses real-time measurements to learn a model of the disturbance, to predict its future behavior. By including this model in the MPC, the latter can proactively counteract the disturbance, significantly improving closed-loop performance. The presented technique includes the disturbance model while preserving robust recursive feasibility and constraint satisfaction. The effectiveness of DL-MPC is demonstrated through simulation of a multivariable nonlinear system, a Continuous-flow Stirred Tank Reactor, subject to periodic disturbances. The results clearly show enhanced tracking accuracy compared to nominal MPC and tube-MPC methods.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1826-1831"},"PeriodicalIF":2.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072396","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687668","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}
{"title":"A New Voltage Regulator for Distribution Networks With Stability and Robustness Certificates","authors":"Nilanjan Roy Chowdhury;Venkatesh Sarangan","doi":"10.1109/LCSYS.2025.3586288","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586288","url":null,"abstract":"This letter considers the voltage regulation problem of a radial and balanced distribution network, in which the impedance values (i.e., resistance and reactance) are uncertain. To solve this problem, we introduce an optimization-based robust control method leveraging tools from Control Lyapunov Function (CLF) and Quadratic Programming (QP). We first show that by selecting a suitable control gain, we can regulate the network voltage towards an arbitrary non-zero sub-level set after a large initial disturbance. Then we provide guidelines for choosing an appropriate CLF such that the aforesaid sub-level set coincides with the voltage safe limits, and thus, ensure voltage stability. Finally, we transform the voltage regulation problem to an equivalent QP-based optimization framework and translate the above conditions to obtain a feasible solution for voltage stability. We also empirically verify the efficacy of our method by performing experiments on the IEEE-33 bus distribution network.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1838-1843"},"PeriodicalIF":2.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687656","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}
{"title":"Optimal Balancing of Tropical Discrete-Event Systems Through Feedback Control","authors":"C. A. Maia","doi":"10.1109/LCSYS.2025.3586634","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586634","url":null,"abstract":"Dynamical Tropical systems are described by means of Tropical Algebra (for instance, Min- or Max-plus ones), which is a kind of idempotent semifield. For such systems, we are interested in the study of general algebraic properties ensuring optimal balancing through feedback control. By balancing, we mean that all events, or transitions, occur at the same rate, meaning that there is no sub-product accumulation inside the system. In this context, after formulating the problem for Tropical Semifields, the first result is the development, thanks to Residuation Theory, of the expression of the maximum feedback matrix expressed in terms of a vector parameter, ensuring that the closed-loop matrix has a desired eigenvalue. Under the assumption of controllability and boundedness of the controllability matrix, we develop a method to properly choose this maximum feedback matrix. In order to illustrate the method, we present a solution for the problem of balancing two unconnected networks by means of feedback control.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1742-1747"},"PeriodicalIF":2.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663716","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}
{"title":"All Data-Driven LQR Algorithms Require at Least as Much Interval Data as System Identification","authors":"Christopher Song;Jun Liu","doi":"10.1109/LCSYS.2025.3586080","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586080","url":null,"abstract":"We show that algorithms for solving continuous-time infinite-horizon LQR problems using input and state data on intervals require at least as much data as system identification. Using this result, we show that the map from interval data to the optimal gain defined by these algorithms is continuous. We then obtain a convergence criterion that allows us to approximate the optimal gain by using sampled data in place of interval data. In doing so, we uncover a connection with the theory of numerical integration. We corroborate our theoretical results with some numerical experiments, which show how judicious selection of sample points can significantly improve the accuracy of the approximation.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1778-1783"},"PeriodicalIF":2.4,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680904","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}
Jonah J. Glunt;Joshua A. Robbins;Jacob A. Siefert;Daniel Silvestre;Herschel C. Pangborn
{"title":"Sharp Hybrid Zonotopes: Set Operations and the Reformulation-Linearization Technique","authors":"Jonah J. Glunt;Joshua A. Robbins;Jacob A. Siefert;Daniel Silvestre;Herschel C. Pangborn","doi":"10.1109/LCSYS.2025.3585953","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3585953","url":null,"abstract":"Mixed integer set representations, and specifically hybrid zonotopes, have enabled new techniques for reachability and verification of nonlinear and hybrid systems. Mixed-integer sets which have the property that their convex relaxation is equal to their convex hull are said to be sharp. This property allows the convex hull to be computed with minimal overhead, and is known to be important for improving the convergence rates of mixed-integer optimization algorithms that rely on convex relaxations. This letter examines methods for formulating sharp hybrid zonotopes and provides sharpness-preserving methods for performing several key set operations. This letter then shows how the reformulation-linearization technique can be applied to create a sharp realization of a hybrid zonotope that is initially not sharp. A numerical example applies this technique to find the convex hull of a level set of a feedforward ReLU neural network.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1802-1807"},"PeriodicalIF":2.4,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671220","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}