IEEE Control Systems Letters最新文献_第6页

H∞ Control With Transients for Linear Time-Varying State-Delay Systems: A Pseudospectral Approach 线性时变状态延迟系统的H∞暂态控制：一种伪谱方法

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-25 DOI: 10.1109/LCSYS.2026.3707174

Junhao Hu;Tao Peng;Zhong Wang;Yan Li

{"title":"H∞ Control With Transients for Linear Time-Varying State-Delay Systems: A Pseudospectral Approach","authors":"Junhao Hu;Tao Peng;Zhong Wang;Yan Li","doi":"10.1109/LCSYS.2026.3707174","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3707174","url":null,"abstract":"This letter investigates the finite-horizon <inline-formula> <tex-math>$H_{infty } $ </tex-math></inline-formula> control problem with explicit transient performance considerations for linear time-varying systems with constant state delay. A history-dependent minimax formulation is first established. By variational analysis, the corresponding first-order optimality conditions are derived and expressed as a delay–advance Hamiltonian boundary value system. To solve this system numerically, a multi-interval pseudospectral discretization is developed, by which the continuous-time delayed finite-horizon <inline-formula> <tex-math>$H_{infty } $ </tex-math></inline-formula> problem is transcribed into a finite-dimensional algebraic problem. The resulting formulation contains the delay-free case as a natural special case. Unlike standard delay-<inline-formula> <tex-math>$H_{infty } $ </tex-math></inline-formula> formulations, which are posed mainly for closed-loop stability and prescribed <inline-formula> <tex-math>$L_{2}$ </tex-math></inline-formula>-gain performance, the joint effect of exogenous disturbances and nonzero initial histories on finite-horizon closed-loop behavior is taken into account in the proposed method. Numerical examples are presented to demonstrate the effectiveness and accuracy of the proposed method.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"1807-1812"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148484144","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}

引用次数: 0

Data-Driven Predictive Control for Stochastic Descriptor Systems: An Innovation-Based Approach Handling Non-Causal Dependencies 随机广义系统的数据驱动预测控制：一种处理非因果依赖的创新方法

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-25 DOI: 10.1109/LCSYS.2026.3707459

Yunxiang Ma;Yibo Wang;Zhongmei Li;Chao Shang

{"title":"Data-Driven Predictive Control for Stochastic Descriptor Systems: An Innovation-Based Approach Handling Non-Causal Dependencies","authors":"Yunxiang Ma;Yibo Wang;Zhongmei Li;Chao Shang","doi":"10.1109/LCSYS.2026.3707459","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3707459","url":null,"abstract":"Descriptor systems arise naturally in real-world applications governed by algebraic constraints, such as power networks, robotics and chemical processes. When a descriptor model contains a nontrivial nilpotent block, the discrete-time input–output map may be improper: the current output depends on future inputs and, in the stochastic case, on future noise terms. This letter proposes a data-driven predictive control framework for stochastic descriptor systems that handles these non-causal dependencies without explicitly identifying system matrices. The key idea is to split fast subsystem into noise-driven and input-driven parts, and then combine the former with the slow subsystem such that an innovation-driven Kalman filter can be appropriately defined to reformulate the stochastic descriptor system into an innovation-driven form. Based on this, a new behavioral system representation is derived, which inspires a data-driven innovation-based multi-step output predictor and a practical Inno-DeePC algorithm that enables data-driven predictive control design without known system matrices while implicitly handling algebraic constraints. Numerical experiments on a DC microgrid demonstrate the effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"1291-1296"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442178","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}

引用次数: 0

Polynomial Internal Models for Finite-Horizon Robust Output Regulation With Unstructured Exogenous Signals 非结构化外源信号有限视界鲁棒输出调节的多项式内模型

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-23 DOI: 10.1109/LCSYS.2026.3706322

Venanzio Cichella;Ean Lovett;Michelangelo Bin;Nicola Mimmo;Lorenzo Marconi

{"title":"Polynomial Internal Models for Finite-Horizon Robust Output Regulation With Unstructured Exogenous Signals","authors":"Venanzio Cichella;Ean Lovett;Michelangelo Bin;Nicola Mimmo;Lorenzo Marconi","doi":"10.1109/LCSYS.2026.3706322","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3706322","url":null,"abstract":"This letter addresses the robust output regulation problem for linear time-invariant (LTI) systems subject to sufficiently smooth, unstructured time-varying disturbances and reference signals. The proposed framework utilizes a polynomial basis to approximate these signals over a finite-time interval. First, we derive an internal model unit (IMU)-based controller which guarantees perfect regulation for polynomial signals of degree up to the selected order. We then extend this synthesis to exogenous signals satisfying suitable smoothness assumptions. By leveraging approximation theory and Input-to-State Stability (ISS) analysis, we prove that the regulation error remains within a neighborhood of zero over <inline-formula> <tex-math>$[0,t_{f}]$ </tex-math></inline-formula>, whose size is governed by the polynomial approximation error and the closed-loop amplification constants. For sufficiently smooth exogenous signals, this residual bound decreases with the polynomial approximation error as the internal-model order increases.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"1303-1308"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11575667","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442220","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}

引用次数: 0

Scalable Design of Attack-Resilient Controllers for Positive Systems 正系统抗攻击控制器的可扩展设计

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-17 DOI: 10.1109/LCSYS.2026.3704261

Alba Gurpegui;Sribalaji C. Anand;André M. H. Teixeira

{"title":"Scalable Design of Attack-Resilient Controllers for Positive Systems","authors":"Alba Gurpegui;Sribalaji C. Anand;André M. H. Teixeira","doi":"10.1109/LCSYS.2026.3704261","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3704261","url":null,"abstract":"This letter proposes a framework for secure and resilient controller design for positive systems against cyber-attacks. In particular, we consider a network-controlled system where an adversary injects false data into the actuator channels to increase the control cost (performance measure) while penalizing the attack effort and subject to state-dependent constraints. Using a minimax formulation, we analyze the worst-case performance loss caused by such adversaries, which is given by the solution of a difference equation, and an algebraic equation when the time horizon is infinite. We show that the optimal attack policy, among possible nonlinear policies, is linear. Despite the lack of explicit stealthiness constraints, we also show that when the measured output has an unstable zero which is not an unstable zero of the performance measure, the attacks can induce unbounded performance degradation. The proposed framework is also extended to systems with model uncertainty. Numerical examples illustrate the results and demonstrate how tools from positive systems and linear regulator theory can be used to mitigate cyber-attacks with low computational effort.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"1255-1260"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442234","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}

引用次数: 0

Chaos-Free Networks Are Stable Recurrent Neural Networks 无混沌网络是稳定的递归神经网络

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-11 DOI: 10.1109/LCSYS.2026.3702800

Stefano De Carli;Davide Previtali;Mirko Mazzoleni;Fabio Previdi

{"title":"Chaos-Free Networks Are Stable Recurrent Neural Networks","authors":"Stefano De Carli;Davide Previtali;Mirko Mazzoleni;Fabio Previdi","doi":"10.1109/LCSYS.2026.3702800","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3702800","url":null,"abstract":"Gated Recurrent Neural Networks (RNNs) are widely used for nonlinear system identification due to their high accuracy, although they often exhibit complex, chaotic dynamics that are difficult to analyze. This letter investigates the system-theoretic properties of the Chaos-Free Network (CFN), an architecture originally proposed to eliminate the chaotic behavior found in standard gated RNNs. First, we formally prove that the CFN satisfies Input-to-State Stability (ISS) by design. However, we demonstrate that the CFN architecture does not intrinsically guarantee Incremental ISS (<inline-formula> <tex-math>$delta $ </tex-math></inline-formula>ISS), as ensuring this property relies on specific parametric constraints. To address this, we introduce the Decoupled-Gate Network (DGN), a novel structural variant of the CFN that removes internal state connections in the gating mechanisms. Finally, we prove that the DGN unconditionally satisfies the <inline-formula> <tex-math>$delta $ </tex-math></inline-formula>ISS property, providing an incrementally stable architecture for identifying nonlinear dynamical systems without requiring complex network training modifications. Numerical results confirm that the DGN maintains the modeling capabilities of standard architectures while adhering to these rigorous stability guarantees.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"751-756"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11558302","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442237","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}

引用次数: 0

Synthesis of Data-Driven Discrete-Time Control Barrier Functions Using Maximal Admissible Sets 基于最大允许集的数据驱动离散控制障碍函数的综合

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-17 DOI: 10.1109/LCSYS.2026.3704517

Farzan Kaviani;Yasaman Pedari;Hamid R. Ossareh

引用次数: 0

Fixed-Time Stabilization of Discrete-Time Switched Linear Systems With Preview Information 带预览信息的离散时间切换线性系统的定时镇定

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-17 DOI: 10.1109/LCSYS.2026.3704098

Flavio Picchiotti;Antoine Girard;Thiago Alves Lima

引用次数: 0

Cooperative Data-Driven Safety Control Based on Distributed Gaussian Processes 基于分布高斯过程的协同数据驱动安全控制

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-24 DOI: 10.1109/LCSYS.2026.3706913

Kento Kanou;Tatsuya Ibuki

引用次数: 0

Linear–Quadratic Gaussian Games With Distributed Sparse Estimation 具有分布稀疏估计的线性二次高斯对策

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-06-15 DOI: 10.1109/LCSYS.2026.3703777

Tianyu Qiu;Filippos Fotiadis;Xinjie Liu;Christian Ellis;Jesse Milzman;Wesley Suttle;Ufuk Topcu;David Fridovich-Keil

{"title":"Linear–Quadratic Gaussian Games With Distributed Sparse Estimation","authors":"Tianyu Qiu;Filippos Fotiadis;Xinjie Liu;Christian Ellis;Jesse Milzman;Wesley Suttle;Ufuk Topcu;David Fridovich-Keil","doi":"10.1109/LCSYS.2026.3703777","DOIUrl":"https://doi.org/10.1109/LCSYS.2026.3703777","url":null,"abstract":"Linear-quadratic Gaussian games provide a framework for modeling strategic interactions in multi-agent systems, where agents must estimate system states from noisy observations while also making decisions to optimize a quadratic cost. However, these formulations usually require agents to utilize the full set of available observations when forming their state estimates, which can be unrealistic in large-scale or resource-constrained settings. In this letter, we study sparse distributed estimation for feedback implementations of linear-quadratic Gaussian (LQG) games with individual noisy observations. Agents implement feedback Nash strategies computed from the corresponding LQG game without measurement noise, while their state estimates are constructed using sparse subsets of available observations. To enforce sparsity in the estimation stage, we design a distributed estimator that balances estimation effectiveness with interagent measurement sparsity via a group lasso problem, while agents implement feedback Nash strategies based on their state estimates. We provide sufficient conditions under which the sparse estimator is guaranteed to trigger a corrective reset to the optimal estimation gain, ensuring that estimation quality does not degrade beyond a level determined by the regularization parameters. Simulations on a formation game show that the proposed approach yields a significant reduction in communication resources consumed while only minimally affecting the nominal equilibrium trajectories. Code is available at: <uri>https://github.com/CLeARoboticsLab/Sensor-Selection</uri>","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"10 ","pages":"1237-1242"},"PeriodicalIF":1.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442460","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}

引用次数: 0

Finite-Time Bipartite Consensus for Multi-Agent Systems With Hidden Markov Switching Topologies 具有隐马尔可夫交换拓扑的多智能体系统的有限时间二部一致性

IF 1.9

IEEE Control Systems Letters Pub Date : 2026-01-01 Epub Date: 2026-09-02 DOI: 10.1109/LCSYS.2026.3730121

Yifang Zhang;Bo Min;James Lam;Ka-Wai Kwok

引用次数: 0