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A Value Function Space Approach for Hierarchical Planning With Signal Temporal Logic Tasks 具有信号时序逻辑任务的层次规划的值函数空间方法
IF 2
IEEE Control Systems Letters Pub Date : 2025-07-10 DOI: 10.1109/LCSYS.2025.3587276
Peiran Liu;Yiting He;Yihao Qin;Hang Zhou;Yiding Ji
{"title":"A Value Function Space Approach for Hierarchical Planning With Signal Temporal Logic Tasks","authors":"Peiran Liu;Yiting He;Yihao Qin;Hang Zhou;Yiding Ji","doi":"10.1109/LCSYS.2025.3587276","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3587276","url":null,"abstract":"Signal Temporal Logic (STL) has emerged as an expressive formal language for reasoning intricate task planning objectives. However, existing STL-based methods often assume full observation and known dynamics of the system, which imposes constraints on real-world applications. To address this challenge, we propose a hierarchical planning framework that starts by constructing the Value Function Space (VFS) for state and action abstraction, which embeds functional information about affordances of the low-level skills. Subsequently, we utilize a neural network to approximate the dynamics in the VFS and employ sampling based optimization to synthesize high-level skill sequences that maximize the robustness measure of the given STL tasks in the VFS. Then those skills are executed in the low-level environment. Empirical evaluations in the Safety Gym and ManiSkill environments demonstrate that our method accomplish the STL tasks without further training in the low-level environments, substantially reducing the training burdens.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1988-1993"},"PeriodicalIF":2.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773302","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
Mutual Information Optimal Control of Discrete-Time Linear Systems 离散线性系统的互信息最优控制
IF 2
IEEE Control Systems Letters Pub Date : 2025-07-10 DOI: 10.1109/LCSYS.2025.3587369
Shoju Enami;Kenji Kashima
{"title":"Mutual Information Optimal Control of Discrete-Time Linear Systems","authors":"Shoju Enami;Kenji Kashima","doi":"10.1109/LCSYS.2025.3587369","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3587369","url":null,"abstract":"In this letter, we formulate a mutual information optimal control problem (MIOCP) for discrete-time linear systems. This problem can be regarded as an extension of a maximum entropy optimal control problem (MEOCP). Differently from the MEOCP where the prior is fixed to the uniform distribution, the MIOCP optimizes the policy and prior simultaneously. As analytical results, under the policy and prior classes consisting of Gaussian distributions, we derive the optimal policy and prior of the MIOCP with the prior and policy fixed, respectively. Using the results, we propose an alternating minimization algorithm for the MIOCP. Through numerical experiments, we discuss how our proposed algorithm works.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1982-1987"},"PeriodicalIF":2.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11075836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773300","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
Leaky-Integrator Echo State Network Incremental ISS Stability Analysis 泄漏积分器回波状态网络增量ISS稳定性分析
IF 2.4
IEEE Control Systems Letters Pub Date : 2025-07-10 DOI: 10.1109/LCSYS.2025.3587362
Hao Deng;Cristina Stoica;Mohammed Chadli
{"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}
引用次数: 0
Priority-Driven Constraints Softening in Safe MPC for Perturbed Systems 摄动系统安全MPC的优先驱动约束软化
IF 2.4
IEEE Control Systems Letters Pub Date : 2025-07-08 DOI: 10.1109/LCSYS.2025.3580494
Ying Shuai Quan;Mohammad Jeddi;Francesco Prignoli;Paolo Falcone
{"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}
引用次数: 0
Leader-Centric Time-Varying Formation Tracking Control for Multi-Agent Systems via Event-Triggered Mechanism 基于事件触发机制的多智能体系统以领导者为中心时变队形跟踪控制
IF 2.4
IEEE Control Systems Letters Pub Date : 2025-07-08 DOI: 10.1109/LCSYS.2025.3586853
Ankush Thakur;Ravi Kiran Akumalla;Tushar Jain
{"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}
引用次数: 0
Periodic Disturbance Learning Model Predictive Control 周期扰动学习模型预测控制
IF 2.4
IEEE Control Systems Letters Pub Date : 2025-07-07 DOI: 10.1109/LCSYS.2025.3586633
Syed Hassan Ahmed;Tommaso Bonetti;Lorenzo Fagiano
{"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}
引用次数: 0
A New Voltage Regulator for Distribution Networks With Stability and Robustness Certificates 一种具有稳定性和鲁棒性的配电网稳压器
IF 2.4
IEEE Control Systems Letters Pub Date : 2025-07-07 DOI: 10.1109/LCSYS.2025.3586288
Nilanjan Roy Chowdhury;Venkatesh Sarangan
{"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}
引用次数: 0
Risk-Sensitive Model Predictive Control for Interaction-Aware Planning–A Sequential Convexification Algorithm 面向交互感知规划的风险敏感模型预测控制——一种序列凸化算法
IF 2
IEEE Control Systems Letters Pub Date : 2025-07-07 DOI: 10.1109/LCSYS.2025.3586667
Renzi Wang;Mathijs Schuurmans;Panagiotis Patrinos
{"title":"Risk-Sensitive Model Predictive Control for Interaction-Aware Planning–A Sequential Convexification Algorithm","authors":"Renzi Wang;Mathijs Schuurmans;Panagiotis Patrinos","doi":"10.1109/LCSYS.2025.3586667","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586667","url":null,"abstract":"This letter considers risk-sensitive model predictive control for stochastic systems with a decision-dependent distribution. This class of systems is commonly found in human-robot interaction scenarios. We derive computationally tractable convex upper bounds to both the objective function, and to frequently used penalty terms for collision avoidance, allowing us to efficiently solve the generally nonconvex optimal control problem as a sequence of convex problems. Simulations of a robot navigating a corridor demonstrate the effectiveness and the computational advantage of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1916-1921"},"PeriodicalIF":2.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725194","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
On Feedback Design for Systems With an Agent in the Loop 环中有Agent系统的反馈设计
IF 2
IEEE Control Systems Letters Pub Date : 2025-07-07 DOI: 10.1109/LCSYS.2025.3586635
J. M. Maestre;F. López-Rodríguez;P. Chanfreut;T. Hatanaka
{"title":"On Feedback Design for Systems With an Agent in the Loop","authors":"J. M. Maestre;F. López-Rodríguez;P. Chanfreut;T. Hatanaka","doi":"10.1109/LCSYS.2025.3586635","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586635","url":null,"abstract":"Systems with agents in the loop introduce new challenges in feedback design due to the dynamic and spatial constraints imposed by the agents’ movement and actuation capabilities. In this letter, we develop a structured framework for designing feedback matrices in such systems while ensuring stability and optimal performance. We formalize the problem by incorporating controllability constraints arising from the agents’ limited ability to actuate at specific locations over time. Our approach leverages a periodic resampling of the system dynamics, allowing for the use of standard feedback design techniques while accounting for the time-varying nature of agent-actuated control. Furthermore, the computation of invariant sets that guarantee constraint satisfaction throughout the execution of the agents’ paths is also addressed. The developed methods are validated on a benchmark system where mobile agents actuate on interconnected subsystems.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"2273-2278"},"PeriodicalIF":2.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072422","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255830","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
Simultaneous Input and State Estimation Under Output Quantization: A Gaussian Mixture Approach 输出量化下的同步输入和状态估计：一种高斯混合方法
IF 2
IEEE Control Systems Letters Pub Date : 2025-07-07 DOI: 10.1109/LCSYS.2025.3586656
Rodrigo A. González;Angel L. Cedeño
{"title":"Simultaneous Input and State Estimation Under Output Quantization: A Gaussian Mixture Approach","authors":"Rodrigo A. González;Angel L. Cedeño","doi":"10.1109/LCSYS.2025.3586656","DOIUrl":"https://doi.org/10.1109/LCSYS.2025.3586656","url":null,"abstract":"Simultaneous Input and State Estimation (SISE) enables the reconstruction of unknown inputs and internal states in dynamical systems, with applications in fault detection, robotics, and control. While various methods exist for linear systems, extensions to systems with output quantization are scarce, and no formal connections to limit Kalman filters are known in this context. This letter addresses these gaps by proposing a novel SISE algorithm for linear systems with quantized output measurements. The proposed algorithm introduces a Gaussian mixture model formulation of the observation model, which leads to closed-form recursive equations in the form of a Gaussian sum filter. In the absence of input prior knowledge, the recursions are shown to converge to a limit-case SISE algorithm, implementable as a bank of linear SISE filters running in parallel. A simulation example is presented to illustrate the effectiveness of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1946-1951"},"PeriodicalIF":2.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725193","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
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