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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel state Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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A port-Hamiltonian framework for displacement-based and rigid formation tracking

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Automatica 2025年 177卷

作者： Li, Ningbo Sun, Zhiyong van der Schaft, Arjan Scherpen, Jacquelien M.A. China Aerodynamics Research and Development Center Mianyang621000 China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China Jan C. Willems Center for Systems and Control University of Groningen Groningen9747 AG Netherlands

This paper proposes a passivity-based port-Hamiltonian (pH) framework for multi-agent displacement-based and rigid formation control and velocity tracking. The control law consists of two parts, where the internal feedback is to track the velocity and the external feedback is to achieve formation stabilization by steering variables of neighboring agents that prescribe the desired geometric shape. Regarding the external feedback, a general framework is proposed for stabilizing different kinds of formations (including displacement-based, distance-based, angle-based, bearing-based and heterogeneous formations) by means of the advantage that the pH model is energy-based and coordinate-free. To solve the issue that the incidence matrix is not of full column rank over cyclic graphs, the graph matrix property is used to prove the convergence to the target sets for the displacement-based formation, while for rigid formations, the algebraic conditions of infinitesimal rigidity are investigated to achieve local asymptotic stability. Furthermore, the rigid formation with heterogeneous constraints is further investigated under this framework and the local asymptotic stability is proved under a mild assumption. Simulations are performed to illustrate the effectiveness of the framework. © 2025 The Author(s)

关键词： Hamiltonians

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Unit commitment with bidirectional ramping constraints of flexibility retrofit thermal power unit

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International Journal of Electrical Power and Energy systems 2025年 168卷

作者： Jiang, Jingxiao Zhu, Yanran Wang, Ying Guo, Xiaorui Lv, Jianhu Qin, Jianxiang Yan, Xingyun Zhang, Kaifeng Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China China Electric Power Research Institute Nanjing210003 China State Grid Ningxia Electric Power Co. Ltd. Yinchuan 750001 China

Flexibility retrofits of thermal power units have been widely implemented to improve power system balancing. These retrofits enable operation below the regular minimum output, known as deep peak regulation, to accommodate increasing renewable energy integration. Due to the inherent characteristics of thermal power units, ramp-up rates and ramp-down rates generally differ. Existing studies often overlook this difference by assuming equal ramping rates. To bridge this gap, this paper systematically models and analyses bidirectional ramping constraints in unit commitment (UC) models, providing a more accurate and realistic representation of the ramping process. Specifically, this paper proposes three innovative bidirectional ramping models. The first is the all-period fixed bidirectional ramping (AFBR) model, which assumes a constant ramp rate across all periods. The second model is the interperiod dynamic bidirectional ramping (InterDBR) model, which captures variations in ramping rates across different peak regulation states, including deep peak regulation with oil (DPRO), deep peak regulation (DPR), and regular peak regulation (RPR). These ramping rate adjustments are restricted to interperiod scheduling periods. The third is the intraperiod dynamic bidirectional ramping (IntraDBR) model, which considers transitions between DPRO, DPR, and RPR within an intraperiod scheduling period, thereby reflecting actual operational conditions of the unit. We validate the effectiveness of the proposed bidirectional ramping models on the IEEE 118-bus system and a real-world Ningxia Power Grid system. Results demonstrate that bidirectional ramping models more accurately and effectively support dispatch scheduling decisions, improving system security and economic efficiency. © 2025 The Authors

关键词： Retrofitting

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Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation

arXiv

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arXiv 2025年

作者： Zhang, Dengke Tang, Quan Liu, Fagui Mei, Haiqing Chen, C.L. Philip The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of New Network Pengcheng Laboratory Shenzhen518000 China The China Tobacco Guangdong Industrial Corporation Guangzhou510385 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Semi-supervised semantic segmentation has witnessed remarkable advancements in recent years. However, existing algorithms are based on convolutional neural networks and directly applying them to Vision Transformers poses certain limitations due to conceptual disparities. To this end, we propose TokenMix, a data augmentation technique specifically designed for semi-supervised semantic segmentation with Vision Transformers. TokenMix aligns well with the global attention mechanism by mixing images at the token level, enhancing learning capability for contextual information among image patches. We further incorporate image augmentation and feature augmentation to promote the diversity of augmentation. Moreover, to enhance consistency regularization, we propose a dual-branch framework where each branch applies image and feature augmentation to the input image. We conduct extensive experiments across multiple benchmark datasets, including Pascal VOC 2012, Cityscapes, and COCO. Results suggest that the proposed method outperforms state-of-the-art algorithms with notably observed accuracy improvement, especially under limited fine annotations. Copyright © 2025, The Authors. All rights reserved.

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Policy iteration optimal tracking control for chaotic systems by using an adaptive dynamic programming approach

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Chinese Physics B 2015年第3期24卷 87-94页

作者：魏庆来刘德荣徐延才 The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.

关键词： adaptive critic designs adaptive dynamic programming approximate dynamic programming neuro-dynamic programming

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Precise planar motion measurement of a swimming multi-joint robotic fish

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Science China(Information Sciences) 2016年第9期59卷 183-197页

作者： Jun YUAN Junzhi YU Zhengxing WU Min TAN State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper presents a method for planar motion measurement of a swimming multi-joint robotic fish. The motion of the robotic fish is captured via image sequences and a proposed tracking scheme is employed to continuously detect and track the robotic fish. The tracking scheme initially acquires a rough scope of the robotic fish and thereafter precisely locates it. Historical motion information is utilized to determine the rough scope, which can speed up the tracking process and avoid possible ambient interference. A combination of adaptive bilateral filtering and k-means clustering is then applied to segment out color markers accurately. The pose of the robotic fish is calculated in accordance with the centers of these markers. Further, we address the problem of time synchronization between the on-board motion control system of the robotic fish and the motion measurement system. To the best of our knowledge, this problem has not been tackled in previous research on robotic fish. With information about both the multi-link structure and motion law of the robotic fish, we convert the problem to a nonlinear optimization problem, which we then solve using the particle swarm optimization(PSO) algorithm. Further, smoothing splines are adopted to fit curves of poses versus time, in order to obtain a continuous motion state and alleviate the impact of noise. Velocity is acquired via a temporal derivative operation. The results of experiments conducted verify the efficacy of the proposed method.

关键词： motion measurement robotic fish time synchronization visual tracking localization

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Double STAR-RIS Enhanced Secure Wireless Communications

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IEEE Transactions on Wireless Communications 2025年

作者： Cai, Yujin Yu, Wenwu Nie, Xiaokai Cheng, Qiang Cui, Tiejun Southeast University School of Mathematics Jiangsu Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently been employed to enhance the secure transmission due to the ability to manipulate the full-space electromagnetic signals. Prior works mainly investigate the single STAR-RIS aided secure communication system, which does not reveal the potential of the cooperative inter-STAR-RIS link. In this paper, a double STAR-RIS enhanced secure communication network involving multiple legitimate users (LUs) and eavesdroppers (Eves) is proposed. For fairness, the minimum secrecy rate maximization problem is formulated by jointly optimizing the active beamforming and passive transmission and reflection (T&R) beamforming. To deal with the highly non-convex nonlinear optimization problem, an active and passive beamforming optimization algorithm is proposed by employing the alternating optimization method. Wherein, a low-complexity sequential constraint relaxation (SCR) based algorithm is designed to solve the passive T&R beamforming optimization problem. Simulation results demonstrate that the secure performance in the double STAR-RIS assisted system outperforms that in the single RIS/double RIS/single STAR-RIS aided network. Furthermore, the proposed algorithm significantly reduces computational time (i.e., resource allocation time) compared with the traditional SCR based beamforming optimization algorithm. © 2002-2012 IEEE.

关键词： Cooperative communication

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Responses of dissolved organic nitrogen to varied nitrogen deposition: A 16-year nitrogen-addition and cessation experiment in a subtropical forest

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Science of the Total Environment 2025年 975卷 179284页

作者： Yang, Dongxing Xie, Dani Mulder, Jan Yu, Qian Huang, Yongmei Duan, Lei State Key Laboratory of Regional Environment and Sustainability School of Environment Tsinghua University Beijing100084 China Shanxi Key Laboratory of Land Consolidation School of Land Engineering Chang'an University Shanxi 710064 China Faculty of Environmental Sciences and Natural Resource Management Norwegian University of Life Sciences Box 5003 ÅsNO-1432 Norway State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment Nanjing University 163 Xian in Ave. Jiangsu Nanjing210023 China Faculty of Geographical Science Beijing Normal University Beijing100875 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Tsinghua University Beijing100084 China

The leaching of dissolved organic nitrogen (DON) signals N loss in forest ecosystems, connecting terrestrial and aquatic ecosystems. The response of DON to varied inorganic N (Nin) deposition remains unclear. A 16-year continuous monitoring of DON in throughfall, soil water, and stream water was conducted under a field N manipulation (10-year Nin addition and subsequent cessation of Nin addition) in a subtropical forest in China. Under reference conditions, the average organic N (Nor) deposition was 23.0 ± 4.9 kg N ha−1 yr−1, with approximately one-third leaching at a soil depth of 30 cm, a value that was higher than those reported for temperate forests. Over a 16-year period, DON concentrations tended to increase in throughfall, soil solutions and stream water. The long-term increase in DON concentrations in soil solutions was primarily driven by increasing Nor deposition and indirectly influenced by decreasing acid deposition. Due to a doubling of monthly Nin input, either as sodium nitrate or as ammonium nitrate, the soil DON leaching doubled, causing the soil to transition from a DON sink to a DON source. After Nin addition ceased, the DON leaching returned to natural levels, and the soil reverted to being a DON sink. This study reveals the importance of Nor deposition and decreasing acid deposition as drivers of long-term trends in DON concentrations in soil solutions, in addition to elucidating the response patterns of DON to increasing and decreasing Nin deposition. © 2025 Elsevier B.V.

关键词： Chronic nitrogen addition Dissolved organic nitrogen Nitrogen deposition Soil acidification recovery Water chemistry

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Effect of New Dual-Credit Policy on Electric Vehicle Diffusion in China

SSRN

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SSRN 2025年

作者： Zhao, Dan Wang, Jian Li, Wen-Wu Huang, Shuai Tang, Jin-Huan School of Management Science and Engineering Anhui University of Technology Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma'anshan243002 China School of Economics and Management Shenyang Aerospace University Shenyang110136 China School of Business Qingdao University Qingdao266071 China

The impact of new dual-credit policy on electric vehicle (EV) diffusion is examined through complex network evolutionary game theory, we find that merely tightening new energy vehicle (NEV) credit rule and corporate average fuel consumption (CAFC) credit rule may not necessarily benefit the growth of auto industry. This paper further discusses the influence of different update strategies on EV diffusion. The results indicate that with the increase of NEV credit accounting coefficient, the upper limit of threshold interval of NEV credit trading price remains unchanged, while lower limit decreases. With the decrease of ratio of standard CAFC to target CAFC or the increase of requirement of NEV credits for fuel vehicle manufacturer, the upper and lower limits of threshold interval of NEV credit price are reduced. With the increasing network scale, the driving effect of Fermi function is gradually superior to EWA algorithm. © 2025, The Authors. All rights reserved.

关键词： Automotive industry

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