IEEE Transactions on Control Systems Technology最新文献

Model Validity in Observers: When to Increase the Complexity of Your Model? 观察者中的模型有效性：何时增加模型的复杂性？

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-03-13 DOI: 10.1109/TCST.2025.3545381

Agapius Bou Ghosn;Philip Polack;Arnaud de La Fortelle

引用次数: 0

Passivation of Clustered DC Microgrids With Non-Monotone Loads 非单调负载集群直流微电网的钝化研究

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-13 DOI: 10.1109/TCST.2025.3537861

Albertus Johannes Malan;Joel Ferguson;Michele Cucuzzella;Jacquelien M. A. Scherpen;Sören Hohmann

引用次数: 0

Data-Driven Combined Longitudinal and Lateral Control for the Car Following Problem 汽车跟随问题的数据驱动纵向和横向联合控制

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-11 DOI: 10.1109/TCST.2025.3539216

Leilei Cui;Sayan Chakraborty;Kaan Ozbay;Zhong-Ping Jiang

{"title":"Data-Driven Combined Longitudinal and Lateral Control for the Car Following Problem","authors":"Leilei Cui;Sayan Chakraborty;Kaan Ozbay;Zhong-Ping Jiang","doi":"10.1109/TCST.2025.3539216","DOIUrl":"https://doi.org/10.1109/TCST.2025.3539216","url":null,"abstract":"This article studies the problem of data-driven combined longitudinal and lateral control of autonomous vehicles (AVs) such that the AV can stay within a safe but minimum distance from its leading vehicle and, at the same time, in the lane. Most of the existing methods for combined longitudinal and lateral control are either model-based or developed by purely data-driven methods such as reinforcement learning. Traditional model-based control approaches are insufficient to address the adaptive optimal control design issue for AVs in dynamically changing environments and are subject to model uncertainty. Moreover, the conventional reinforcement learning approaches require a large volume of data, and cannot guarantee the stability of the vehicle. These limitations are addressed by integrating the advanced control theory with reinforcement learning techniques. To be more specific, by utilizing adaptive dynamic programming (ADP) techniques and using the motion data collected from the vehicles, a policy iteration algorithm is proposed such that the control policy is iteratively optimized in the absence of the precise knowledge of the AV’s dynamical model. Furthermore, the stability of the AV is guaranteed with the control policy generated at each iteration of the algorithm. The efficiency of the proposed approach is validated by the integrated simulation of SUMO and CommonRoad.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 3","pages":"991-1005"},"PeriodicalIF":4.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883414","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

Q-Learning-Based Optimal Control via Adaptive Critic Network for a Wankel Rotary Engine 基于q学习的Wankel旋转发动机自适应评价网络最优控制

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-04 DOI: 10.1109/TCST.2025.3533312

Anthony Siming Chen;Guido Herrmann;Reza Islam;Chris Brace;James W. G. Turner;Stuart Burgess

引用次数: 0

Constraint-Adaptive Model Predictive Control for Radio Frequency Hyperthermia Cancer Treatments 射频热疗癌症治疗的约束自适应模型预测控制

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-04 DOI: 10.1109/TCST.2025.3533315

S. A. N. Nouwens;M. M. Paulides;W. P. M. H. Heemels

{"title":"Constraint-Adaptive Model Predictive Control for Radio Frequency Hyperthermia Cancer Treatments","authors":"S. A. N. Nouwens;M. M. Paulides;W. P. M. H. Heemels","doi":"10.1109/TCST.2025.3533315","DOIUrl":"https://doi.org/10.1109/TCST.2025.3533315","url":null,"abstract":"During a mild hyperthermia treatment, tumors are heated to temperatures ranging from <inline-formula> <tex-math>$39~^{circ } $ </tex-math></inline-formula>C to <inline-formula> <tex-math>$45~^{circ } $ </tex-math></inline-formula>C for 60–90 min. This thermal therapy can be a successful adjuvant to conventional cancer treatments such as chemotherapy and radiotherapy. In order to extract the maximum potential from the thermal therapy, it is crucial to heat the tumor to the desired therapeutic temperature while minimally heating the healthy tissue. Due to the recent development of magnetic resonance (MR)-compatible heating devices, MR thermometry techniques can be employed to noninvasively monitor the internal patient temperature in real time. This development enables closed-loop control strategies to improve the clinical value of the hyperthermia treatment. In this article, we propose a novel model predictive control (MPC) solution based on the alternating direction method of multipliers in combination with constraint removal techniques to compute optimal control inputs for radio frequency (RF)-based mild hyperthermia in real time based on models with <inline-formula> <tex-math>$10^{5}$ </tex-math></inline-formula>–<inline-formula> <tex-math>$10^{6}$ </tex-math></inline-formula> states and temperature safety constraints. We validated the proposed controller on high-fidelity patient models with and without patient model mismatches. We will show that the proposed control strategy can track a desired tumor temperature reference, while ensuring patient safety through <inline-formula> <tex-math>$10^{5}$ </tex-math></inline-formula>–<inline-formula> <tex-math>$10^{6}$ </tex-math></inline-formula> constraints and maintaining real-time feasibility with a computation time of 6 s, which is sufficiently fast considering the thermal dynamics.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 3","pages":"1021-1036"},"PeriodicalIF":4.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883424","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

Trajectory Planning of Radio Source Tracking for the New Feed Cabin Mechanism in FAST FAST新型馈源座舱机构的射电源跟踪轨迹规划

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-04 DOI: 10.1109/TCST.2025.3534531

Bin Zhang;Zhaoyang Li;Xiaoyan Wang;Weiwei Shang;Xinyu Gao;Yifan Ma;Rui Yao;Hui Li;Jianing Yin;Qingge Yang;Qingwei Li

{"title":"Trajectory Planning of Radio Source Tracking for the New Feed Cabin Mechanism in FAST","authors":"Bin Zhang;Zhaoyang Li;Xiaoyan Wang;Weiwei Shang;Xinyu Gao;Yifan Ma;Rui Yao;Hui Li;Jianing Yin;Qingge Yang;Qingwei Li","doi":"10.1109/TCST.2025.3534531","DOIUrl":"https://doi.org/10.1109/TCST.2025.3534531","url":null,"abstract":"To reduce the weight of the feed cabin and increase the observation range of the five-hundred-meter aperture spherical radio telescope (FAST) for reaching the galactic center, a new feed cabin mechanism (NFCM) with a lightweight nine-cable-driven structure has recently been proposed, which theoretically has satisfactory performance for the forthcoming upgrade of FAST. However, trajectory planning suitable for the NFCM is still lacking when tracking radio sources. Consequently, an optimal trajectory planning method is proposed in this article that can achieve smooth motion of the NFCM within a specific period by considering the observation requirements of FAST. Based on the motion analysis for radio source tracking, the trajectory relationship between the radio source and the NFCM is deduced by considering the rotation of the Earth. Then, based on the quintic B-spline, the observation-related cable force characteristics are designed as the objective function to obtain the optimal trajectory of the NFCM, where multiple constraints in different spaces are uniformly mapped to the observation space for optimization complexity reduction by using the graphic-based method. The simulation results show that the optimized observation trajectory of the NFCM using constraint mapping is smooth enough to track the radio source, which brings an acceptable continuity of cable length variation for effectively reducing the potential mechanical shock, and the cable force characteristics with constraints are also well guaranteed. In addition, the effectiveness of constraints, the optimality of cable force characteristics, and the feasibility of the planned trajectory are further demonstrated in simulations.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 3","pages":"1051-1068"},"PeriodicalIF":4.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883469","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

Robust Predictive Motion Planning by Learning Obstacle Uncertainty 基于学习障碍不确定性的鲁棒预测运动规划

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-03 DOI: 10.1109/TCST.2025.3533378

Jian Zhou;Yulong Gao;Ola Johansson;Björn Olofsson;Erik Frisk

{"title":"Robust Predictive Motion Planning by Learning Obstacle Uncertainty","authors":"Jian Zhou;Yulong Gao;Ola Johansson;Björn Olofsson;Erik Frisk","doi":"10.1109/TCST.2025.3533378","DOIUrl":"https://doi.org/10.1109/TCST.2025.3533378","url":null,"abstract":"Safe motion planning for robotic systems in dynamic environments is nontrivial in the presence of uncertain obstacles, where estimation of obstacle uncertainties is crucial in predicting future motions of dynamic obstacles. The worst case characterization gives a conservative uncertainty prediction and may result in infeasible motion planning for the ego robotic system. In this article, an efficient, robust, and safe motion-planning algorithm is developed by learning the obstacle uncertainties online. More specifically, the unknown yet intended control set of obstacles is efficiently computed by solving a linear programming (LP) problem. The learned control set is used to compute forward reachable sets (FRSs) of obstacles that are less conservative than the worst case prediction. Based on the forward prediction, a robust model predictive controller is designed to compute a safe reference trajectory for the ego robotic system that remains outside the reachable sets of obstacles over the prediction horizon. The method is applied to a car-like mobile robot in both simulations and hardware experiments to demonstrate its effectiveness.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 3","pages":"1006-1020"},"PeriodicalIF":4.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883468","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

Switching Frequency Limitation With Finite Control Set Model Predictive Control via Slack Variables 有限控制集开关频率限制模型的松弛变量预测控制

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-02-03 DOI: 10.1109/TCST.2025.3527876

Luca M. Hartmann;Orcun Karaca;Tinus Dorfling;Tobias Geyer

引用次数: 0

Sensitivity-Based Distributed NMPC: Experimental Results for a Levitating Planar Motion System 基于灵敏度的分布式NMPC：悬浮平面运动系统的实验结果

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-01-24 DOI: 10.1109/TCST.2025.3530165

Maximilian Pierer von Esch;Eva Nistler;Andreas Völz;Knut Graichen

引用次数: 0

Autonomous Hook-Based Grasping and Transportation With Quadcopters 四轴飞行器的自动挂钩抓取和运输

IF 4.9 2区计算机科学

IEEE Transactions on Control Systems Technology Pub Date : 2025-01-23 DOI: 10.1109/TCST.2025.3529356

Péter Antal;Tamás Péni;Roland Tóth

{"title":"Autonomous Hook-Based Grasping and Transportation With Quadcopters","authors":"Péter Antal;Tamás Péni;Roland Tóth","doi":"10.1109/TCST.2025.3529356","DOIUrl":"https://doi.org/10.1109/TCST.2025.3529356","url":null,"abstract":"Payload grasping and transportation with quadcopters is an active research area that has rapidly developed over the last decade. To grasp a payload without human interaction, most state-of-the-art approaches apply robotic arms that are attached to the quadcopter body. However, due to the large weight and power consumption of these aerial manipulators, their agility and flight time are limited. This article proposes a motion control and planning method for transportation with a lightweight, passive manipulator structure that consists of a hook attached to a quadrotor using a 1-DoF revolute joint. To perform payload grasping, transportation, and release, first, time-optimal reference trajectories are designed through specific waypoints to ensure the fast and reliable execution of the tasks. Then, a two-stage motion control approach is developed based on a robust geometric controller for precise and reliable reference tracking and a linear-quadratic payload regulator for rapid setpoint stabilization of the payload swing. Furthermore, mathematical guarantees are provided for closed-loop stability to ensure safe operation. The proposed control architecture and design are evaluated in a high-fidelity physical simulator and also in real flight experiments, using a custom-made quadrotor-hook manipulator platform.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 3","pages":"980-990"},"PeriodicalIF":4.9,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883467","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