Yongcan Cao;Lixian Zhang;Abhinav Sinha;Xiaocong Li;Yanan Li;Jun Ma;Silu Chen;Zhaodan Kong
{"title":"Guest Editorial: Special Section on Safety, Robustness, and Effectiveness in Human–Machine Teaming","authors":"Yongcan Cao;Lixian Zhang;Abhinav Sinha;Xiaocong Li;Yanan Li;Jun Ma;Silu Chen;Zhaodan Kong","doi":"10.1109/LCSYS.2025.3614081","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3614081","url":null,"abstract":"","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2271-2272"},"PeriodicalIF":2.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11195958","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255814","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":"Robustness Analysis for Quantum Systems Controlled by Continuous-Time Pulses","authors":"S. P. O’Neil;E. A. Jonckheere;S. Schirmer","doi":"10.1109/LCSYS.2025.3617038","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3617038","url":null,"abstract":"Differential sensitivity techniques originally developed to study the robustness of energy landscape controllers are generalized to the important case of closed quantum systems subject to continuously varying controls. Vanishing sensitivity to parameter variation is shown to coincide with perfect fidelity, as was the case for time-invariant controls. Upper bounds on the magnitude of the differential sensitivity to any parameter variation are derived based simply on knowledge of the system Hamiltonian and the maximum size of the control inputs.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2345-2350"},"PeriodicalIF":2.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255841","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":"On Variance-Reduced Extragradient Methods for Stochastic Generalized Nash Equilibrium Problems","authors":"Barbara Franci","doi":"10.1109/LCSYS.2025.3615593","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3615593","url":null,"abstract":"We study variance reduction schemes for stochastic generalized Nash equilibrium problems. Specifically, we consider two instances of the extragradient algorithm to find a Nash equilibrium and show their convergence under weaker assumptions than the literature. In the particular case where we can write the cost function as a finite sum, we also propose a novel approximation scheme that sensibly lowers the computational burden. Numerical simulations suggest that the performance of the new approximation scheme can improve the computations also in the fully stochastic (infinite) case.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2333-2338"},"PeriodicalIF":2.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255807","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":"Time-Constrained Consensus With Reduced Agent Interactions for Matrix-Scaled Networks","authors":"K. P. Sunny;Rakesh R. Warier","doi":"10.1109/LCSYS.2025.3614183","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3614183","url":null,"abstract":"This letter proposes a distributed control method for matrix-scaled multi-agent networks aimed at achieving practical convergence within a user-defined time frame. The control law of each individual agent relies only on information from neighboring agents and is updated at discrete intervals determined by state-dependent triggering functions, reducing the frequency of agent interactions. To this end, first, the controller is augmented with a time-varying gain. Then, the dynamics of the closed-loop system over the finite-time interval is transformed into an infinite-time frame using time scaling. Lyapunov-based analysis is employed to derive suitable triggering conditions that guarantee the asymptotic convergence of the time-transformed system, thereby ensuring the prescribed-time convergence of the original system. Furthermore, a practical prescribed-time event-triggered control scheme is proposed that excludes Zeno behavior. Simulation results validate the effectiveness of the proposed controller, even in the presence of external disturbances.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2259-2264"},"PeriodicalIF":2.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210071","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":"Control of Subpopulation Fractions in a Population of Bistable Cells","authors":"Dylan Hirsch;Sylvia Herbert","doi":"10.1109/LCSYS.2025.3613753","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3613753","url":null,"abstract":"Bistable genetic circuits have long been studied in systems and synthetic biology, with notable recent work focused on controlling the phenotypic composition of populations with such circuits. Here, we build on previous literature to theoretically characterize a mechanism by which cells with bistable circuits can use quorum sensing to drive the population to arbitrary phenotypic compositions. We in particular investigate the ability of a proportional controller to accomplish this task on ideal and non-ideal plants, providing performance guarantees and, under additional assumptions, guarantees of almost-global convergence to a desirable population equilibrium.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2253-2258"},"PeriodicalIF":2.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210073","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}
Tochukwu E. Ogri;Muzaffar Qureshi;Zachary I. Bell;Wanjiku A. Makumi;Rushikesh Kamalapurkar
{"title":"An Output Feedback Approach to Differential Graphical Games in Linear Multiagent Systems","authors":"Tochukwu E. Ogri;Muzaffar Qureshi;Zachary I. Bell;Wanjiku A. Makumi;Rushikesh Kamalapurkar","doi":"10.1109/LCSYS.2025.3612938","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3612938","url":null,"abstract":"This letter presents an output feedback approach to distributed optimal formation control of linear time-invariant multiagent systems. The formation control problem is formulated as a differential graphical game problem. It is assumed that each agent receives partial error-states of its immediate neighbors. To account for the dependence of the value function of each agent on the error-states of its extended neighbors, a robust observer that estimates the error-states of the extended neighbors using partial error-states of the immediate neighbors is designed. The observer is integrated with a controller to approximate a global feedback Nash equilibrium (FNE) solution of the differential graphical game. Stability of the closed-loop system and convergence of the estimated value functions to the approximate FNE solution are established using a Lyapunov-based analysis. Simulations demonstrate the efficacy of the developed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2265-2270"},"PeriodicalIF":2.0,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255895","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":"Accelerating Distributed Average Consensus in Wireless Sensor Networks via GNN-Based Broadcast Probability Optimization","authors":"Miao Jiang;Zhong Hu;Yiqing Li","doi":"10.1109/LCSYS.2025.3612955","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3612955","url":null,"abstract":"Achieving efficient distributed average consensus is crucial for collaborative applications in wireless sensor networks (WSNs). Traditional gossip-based methods encounter difficulties in balancing communication efficiency and consensus rate, especially in dynamic and resource-constrained wireless environments. To overcome these challenges, a graph neural network (GNN), specifically the message passing neural network (MPNN) framework, is proposed to optimize node broadcast probabilities for the probabilistic broadcast gossip scheme. By employing MPNN with attention mechanisms, the proposed method dynamically allocates broadcast probabilities based on both local node characteristics and global network topologies. Extensive simulations reveal that the proposed method significantly surpasses heuristic and optimization-based baselines, achieving a substantial reduction in communication costs. These results highlight the potential of GNNs in advancing distributed consensus protocols for WSNs.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2247-2252"},"PeriodicalIF":2.0,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210072","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":"Event-Triggered Predictor-Based Control of Networked Systems With Input Delays","authors":"Mani H. Dhullipalla;Dimos V. Dimarogonas","doi":"10.1109/LCSYS.2025.3611422","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3611422","url":null,"abstract":"Modern wireless systems can accurately estimate network latencies; this information could help design better controllers for systems prone to large delays. In this letter, we consider the problem of event-triggered control of linear networked systems with known input delays and address it via hybrid system approach. Specifically, we design a predictor-based state observer that incorporates input delay and propagated outputs to estimate the future state of the system. Subsequently, this estimated state is utilized to generate control inputs for transmissions over the network. In order to reduce the number of transmissions, we design a dynamic event-triggering mechanism (ETM) which makes decisions on whether or not to transmit the control inputs at pre-defined instants. The ETM, by its design, is devoid of Zeno behavior.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2223-2228"},"PeriodicalIF":2.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141721","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}
Ran Jing;Charles Van Hook;Ilyoung Yang;Andrew P. Sabelhaus
{"title":"Fault Detection and Response for Safe Control of Artificial Muscles in Soft Robots","authors":"Ran Jing;Charles Van Hook;Ilyoung Yang;Andrew P. Sabelhaus","doi":"10.1109/LCSYS.2025.3610637","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3610637","url":null,"abstract":"Robots built from soft materials have the potential for intuitively-safer interactions with humans and the environment. However, soft robots’ embodiments have many sources of failure that could lead to unsafe conditions in closed-loop control, such as degradation of sensors or fracture of actuators. This letter proposes a fault detection system for sensors attached to artificial muscle actuators that satisfies a formal safety condition. Our approach combines redundant sensing, model-based state estimation, and Gaussian process regression to determine when one sensor’s reading statistically diverges from another, indicating a fault condition. We apply the approach to electrothermal shape memory alloy (SMA) artificial muscles, demonstrating that our method prevents the overheating and fire damage risk that could otherwise occur. Experiments show that when the muscle’s nominal sensor (temperature via a thermocouple) is fractured from the robot, the redundant sensor (electrical resistance) combined with our method prevents violation of state constraints. Deploying this system in real-world human-robot interaction could help make soft robots more robust and reliable.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2321-2326"},"PeriodicalIF":2.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11165112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255810","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 Optimal Deterministic Policy Learning in Chance-Constrained Markov Decision Processes","authors":"Hongyu Yi;Chenbei Lu;Chenye Wu","doi":"10.1109/LCSYS.2025.3610666","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3610666","url":null,"abstract":"Constrained Markov Decision Processes (CMDPs) are widely used for online decision-making under constraints. However, their applicability is often limited by the reliance on expectation-based linear constraints. Chance-Constrained MDPs (CCMDPs) address this by incorporating nonlinear, probabilistic constraints, yet are often intractable and approximated via CVaR-based reformulations. In this letter, we propose a tractable framework for CCMDPs to exactly solve the best deterministic policies based on a three-stage, model-based constraint learning algorithm. Theoretically, we establish a polynomial sample complexity guarantee for feasible policy optimization using a novel distributional concentration analysis. A case study on a thermostatically controlled load demonstrates the effectiveness of our approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2217-2222"},"PeriodicalIF":2.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141719","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}