IEEE Transactions on Control Systems Technology最新文献_第9页

Hybrid Control for Improved Pressure and Flow Tracking in Mechanical Ventilation 改进机械通气压力和流量跟踪的混合控制

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-02-27 DOI: 10.1109/TCST.2026.3661100

Lars van de Kamp;Isabelle Franklin;Bas van Loon;Nathan van de Wouw;Tom Oomen

引用次数: 0

Robust Control of Autonomous Remotely Operated Vehicles at Exposed Aquaculture Sites 水产养殖场所自主遥控车辆的鲁棒控制

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-02-23 DOI: 10.1109/TCST.2026.3662005

Kenny Hoang Nguyen;Walter Caharija;Sveinung Johan Ohrem;Jan Tommy Gravdahl;Antonio Loría;Herman Biørn Amundsen

{"title":"Robust Control of Autonomous Remotely Operated Vehicles at Exposed Aquaculture Sites","authors":"Kenny Hoang Nguyen;Walter Caharija;Sveinung Johan Ohrem;Jan Tommy Gravdahl;Antonio Loría;Herman Biørn Amundsen","doi":"10.1109/TCST.2026.3662005","DOIUrl":"https://doi.org/10.1109/TCST.2026.3662005","url":null,"abstract":"This article presents two adaptive nonlinear controllers for robust velocity and heading control of a remotely operated vehicle (ROV) navigating in exposed aquaculture sites. The controllers are designed to enable autonomous traversal of an aquaculture net pen using a net-following guidance algorithm in the presence of significant environmental disturbances. Each controller is tailored for different application scenarios, hence for different models of the ROV. The first is suitable for slow-speed maneuvers, while the second applies to cases involving aggressive maneuvers. This model is more complex due to the additional Coriolis force nonlinearities that appear in the second scenario. For the closed-loop system with the first controller, we prove uniform global exponential stability. For the second controller, we establish uniform asymptotic stability under a necessary and sufficient condition of persistence of excitation. Furthermore, both controllers achieve estimation of the (constant) ocean currents. In addition, our theoretical findings are reinforced by simulation and experimental results that illustrate the good performance of our controllers. The experimental tests were realized on an industrial underwater robot. Furthermore, the first controller was successfully tested at a full-scale aquaculture site under realistic operational conditions.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 3","pages":"1232-1247"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148505561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bézier Curve-Based Optimization Framework for Multirobot Motion Planning in Unknown Environments 未知环境下基于bsamzier曲线的多机器人运动规划优化框架

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI: 10.1109/TCST.2026.3659194

Amna Mazen;Mariam Faied;Mohan Krishnan

{"title":"Bézier Curve-Based Optimization Framework for Multirobot Motion Planning in Unknown Environments","authors":"Amna Mazen;Mariam Faied;Mohan Krishnan","doi":"10.1109/TCST.2026.3659194","DOIUrl":"https://doi.org/10.1109/TCST.2026.3659194","url":null,"abstract":"In recent years, multirobot systems (MRSs) have witnessed significant growth because of their capability of solving complex problems involving collaborative missions. A two-phase approach is typically employed in such applications, encompassing task planning and assignment among the robots, followed by motion planning to execute the assigned tasks. This work focuses on the motion planning phase, which facilitates the optimal navigation of multiple robots from their initial to desired goal configurations. A novel multirobot Bézier curve-based trajectory planner (MrBTP) is proposed. MrBTP generates optimal trajectories for multiple robots navigating in an unknown environment, including the polygonal characterization of the available open space. The optimization process is based on using a weighted objective function that combines the navigation time of each robot and the length of its trajectory, allowing for various path optimization strategies. The effectiveness of MrBTP has been evaluated in various scenarios, and its performance is compared with that of a selected trajectory planner based on three performance metrics. Over the three robots used in the test, MrBTP reduced the navigation time by 21%–49% and the trajectory length by 10%–18% compared to the selected benchmark trajectory planner. In addition, it ensures <inline-formula> <tex-math>$C^{2}$ </tex-math></inline-formula> rather than just <inline-formula> <tex-math>$C^{1}$ </tex-math></inline-formula> continuity.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 3","pages":"1248-1258"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148505564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Heat Generation Systems Through Transformer and Recurrent Neural Forecasting Combined With Mixed-Integer Predictive Control 变压器和循环神经预测结合混合整数预测控制的高效产热系统

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-02-18 DOI: 10.1109/TCST.2026.3662753

Diyar Altinses;Marlon Löppenberg;Andreas Schwung

{"title":"Efficient Heat Generation Systems Through Transformer and Recurrent Neural Forecasting Combined With Mixed-Integer Predictive Control","authors":"Diyar Altinses;Marlon Löppenberg;Andreas Schwung","doi":"10.1109/TCST.2026.3662753","DOIUrl":"https://doi.org/10.1109/TCST.2026.3662753","url":null,"abstract":"Accurate heat demand forecasting and control are critical for optimizing the operational efficiency of thermal energy systems, including power plants and district heating networks. This work presents a receding horizon control framework for optimizing heat production in district energy systems under real-world operational conditions. The proposed controller minimizes production costs while considering electricity market prices, which significantly affect the economic performance of heat generation units. The system coordinates multiple heterogeneous generation assets under mixed-integer programming constraints. To support the controller, we develop a forecasting framework that combines transformer and gated recurrent unit (GRU) architectures to improve prediction accuracy. This hybrid model utilizes multivariate input features, including ambient temperature and historical thermal output, to generate robust and probabilistic forecasts. The Transformer captures long-range dependencies in the data, while the GRU models temporal sequences and cyclical behavior. Experimental results on real-world data demonstrate that this method can reduce total operational costs by 16.3% and enhance resource efficiency in thermal energy production, providing a scalable solution for smart energy management.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 3","pages":"1259-1271"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148506663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Two-Stage Motion Planning Algorithm Combining Geometric Heat Flow and Fine-Tuning 一种结合几何热流和微调的两阶段运动规划算法

IF 3.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-01-21 DOI: 10.1109/TCST.2026.3654153

Jixiang Chen;Shenyu Liu

{"title":"A Two-Stage Motion Planning Algorithm Combining Geometric Heat Flow and Fine-Tuning","authors":"Jixiang Chen;Shenyu Liu","doi":"10.1109/TCST.2026.3654153","DOIUrl":"https://doi.org/10.1109/TCST.2026.3654153","url":null,"abstract":"In this work, we address the problem of motion planning for control-affine systems. We first employ the geometric heat flow (GHF) method to generate an admissible trajectory that adheres to kinematic constraints and ensures obstacle avoidance. However, due to inherent limitations of GHF, the resulting trajectory’s final state may deviate from the goal state. To address this issue, we introduce a novel gradient descent algorithm for fine-tuning, which iteratively adjusts the trajectory to minimize the final state error while maintaining compliance with kinematic and obstacle avoidance constraints, and ensuring that the control effort remains reasonably small. By leveraging a novel barrier function based on superellipses during both GHF and fine-tuning stages, our motion planning algorithm reduces conservativeness in collision avoidance between rectangular objects and obstacles. We validate our approach through simulation examples and comparison with other motion planning algorithms for tractor-trailer models, confirming its efficacy and efficiency in generating intricate maneuvers for control-affine systems in complex operational spaces.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 3","pages":"1600-1607"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint Trajectory and Tracking Controller Design Under Uncertain Models: Study With Autonomous Parafoils 不确定模型下的关节轨迹与跟踪控制器设计：自主伞翼的研究

IF 3.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-04-09 DOI: 10.1109/TCST.2026.3672897

Dennis Gramlich;Lukas Hewing;Carsten W. Scherer;Valentin Preda;Joost Veenman;Carlos Ardura;Samir Bennani;Christian Ebenbauer

{"title":"Joint Trajectory and Tracking Controller Design Under Uncertain Models: Study With Autonomous Parafoils","authors":"Dennis Gramlich;Lukas Hewing;Carsten W. Scherer;Valentin Preda;Joost Veenman;Carlos Ardura;Samir Bennani;Christian Ebenbauer","doi":"10.1109/TCST.2026.3672897","DOIUrl":"https://doi.org/10.1109/TCST.2026.3672897","url":null,"abstract":"This article advocates the use of robust optimization methods for trajectory planning in control systems, highlighting their potential to enhance system robustness and performance. We provide an extensive benchmark of robust differential dynamic programming (DDP), a method that jointly optimizes reference trajectories and tracking controllers to reduce sensitivity to uncertainties. The optimized trajectories avoid regions of high uncertainty in the state space and mitigate the excitation of uncertain system components. We evaluate the performance of these robust trajectories using a parafoil landing simulator developed to industrial standards, demonstrating superior landing accuracy compared to nominal trajectories. Furthermore, we show that robust trajectories autonomously implement energy management strategies, such as spiraling over a landing point to dissipate excess altitude, which are often hard-coded in parafoil guidance algorithms. Our results underscore the potential of robust trajectory planning to advance control system design.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 3","pages":"1465-1480"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hierarchical Data-Driven Koopman Model Predictive Control for Grid-Interactive Efficient Operation of Variable Refrigerant Flow System Combined With Dedicated Outdoor Air System 结合专用室外空气系统的变冷流量系统网格交互高效运行的分层数据驱动Koopman模型预测控制

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2025-11-12 DOI: 10.1109/TCST.2025.3624361

Chao Pan;Yaoyu Li

{"title":"A Hierarchical Data-Driven Koopman Model Predictive Control for Grid-Interactive Efficient Operation of Variable Refrigerant Flow System Combined With Dedicated Outdoor Air System","authors":"Chao Pan;Yaoyu Li","doi":"10.1109/TCST.2025.3624361","DOIUrl":"https://doi.org/10.1109/TCST.2025.3624361","url":null,"abstract":"For grid-interactive building operations, variable refrigerant flow (VRF) systems with variable speed drives are appealing sources. Often combined with a dedicated outdoor air system (DOAS) for ventilation, the VRF-DOAS presents higher complexity for control design. This article proposes a hierarchical Koopman model predictive control (MPC) strategy for the VRF-DOAS system to achieve demand response (DR) operation at the upper layer and frequency regulation (FR) at the lower layer. For the lower layer, an offset-free Koopman MPC is designed to achieve FR tracking with more robustness. To achieve a deeper FR operation, the high-bandwidth RegD FR is targeted with the VRF compressor power. For computationally efficient MPC design, data-driven Koopman models of different time scales are used, which facilitates convex MPC design. The upper layer MPC yields thermal regulation and power References, passed to the lower layer with an interpolation scheme with a more consistent prediction horizon, instead of a shrinking horizon, for MPC design. The proposed control is evaluated with FMI-based co-simulation, where a Modelica-based dynamic simulation model of VRF-DOAS is orchestrated with the MPC design in Python. Simulation results show that the proposed control method can achieve both quality FR performance scores and DR performance, besides satisfactory thermal regulation. The proposed method reduces the net energy cost by 8.2% for a 24-h simulation.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 2","pages":"584-600"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148485168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Collaborative Drill Alignment in Surgical Robotics 手术机器人中的协同钻头对准

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2025-12-23 DOI: 10.1109/TCST.2025.3642901

Daniel Larby;Joshua Kershaw;Matthew Allen;Fulvio Forni

{"title":"Collaborative Drill Alignment in Surgical Robotics","authors":"Daniel Larby;Joshua Kershaw;Matthew Allen;Fulvio Forni","doi":"10.1109/TCST.2025.3642901","DOIUrl":"https://doi.org/10.1109/TCST.2025.3642901","url":null,"abstract":"Robotic assistance allows surgeries to be reliably and accurately executed while still under the direct supervision of the surgeon, combining the strengths of robotic technology with the surgeon’s expertise. This article describes a robotic system designed to assist in surgical procedures by implementing a virtual drill guide. The system integrates virtual-fixture functionality using a novel virtual-mechanism controller with additional visual feedback. The controller constrains the tool to the desired axis, while allowing axial motion to remain under the surgeon’s control. Compared to prior virtual-fixture approaches—which primarily perform pure energy-shaping and damping injection with linear springs and dampers–our controller uses a virtual prismatic joint to which the robot is constrained by nonlinear springs, allowing us to easily shape the dynamics of the system. We detail the calibration procedures required to achieve sufficient precision and describe the implementation of the controller. We apply this system to a veterinary procedure: drilling for transcondylar screw placement in dogs. The results of the trials on 3D-printed bone models demonstrate sufficient precision to perform the procedure and suggest improved angular accuracy and reduced exit translation errors compared to patient-specific guides (PSGs). Discussion and future improvements follow.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 2","pages":"878-891"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148485282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Controller for Robot Manipulators in Task-Space With Visual-Inertial Feedback 具有视觉-惯性反馈的任务空间机器人混合控制器

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI: 10.1109/TCST.2025.3631985

Seyed Hamed Hashemi;Jouni Mattila

{"title":"Hybrid Controller for Robot Manipulators in Task-Space With Visual-Inertial Feedback","authors":"Seyed Hamed Hashemi;Jouni Mattila","doi":"10.1109/TCST.2025.3631985","DOIUrl":"https://doi.org/10.1109/TCST.2025.3631985","url":null,"abstract":"This article presents a visual-inertial-based control strategy to address the task-space control problem for robot manipulators. To achieve this, a hybrid observer is introduced for visual-inertial odometry, enabling the control loop to be closed directly in Cartesian space by estimating the end-effector pose. The end-effector is equipped with an inertial measurement unit (IMU) and a stereo camera, which provide task-space feedback information to the proposed observer. A hybrid controller is then designed to utilize the estimated end-effector pose for accurate motion control. The Lyapunov stability theorem is employed to demonstrate that the resulting closed-loop system, using the proposed observer-based controller, is globally and asymptotically stable. Besides this notable merit (global asymptotic stability), the proposed method also reduces the impact of robot kinematics on the controller’s performance. Real-world experiments and computer simulations using a six-degrees-of-freedom (DoFs) long-reach hydraulic robot manipulator are conducted to evaluate the performance of the proposed observer-based control scheme.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"34 2","pages":"737-746"},"PeriodicalIF":4.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11272969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148485396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Risk-Averse Motion Planning for Quadrotors Using Conditional Value-at-Risk 使用条件风险值的四旋翼飞行器的风险厌恶运动规划

IF 4.4 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2026-03-01 Epub Date: 2026-02-23 DOI: 10.1109/TCST.2026.3663687

Xiang Yu;Jun Bian;Jianchun Zhang;Kexin Guo

引用次数: 0