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Multi-timescale Reward-based DRL Energy Management for Regenerative Braking Energy Storage System

IEEE Transactions on Transportation Electrification 2025年第3期11卷 7488-7500页

作者： Chen, Junyu Zhao, Yue Wang, Minghao Yang, Kai Ge, Yinbo Wang, Ke Lin, Hongjian Pan, Pengyu Hu, Haitao He, Zhengyou Xu, Zhao Southwest Jiaotong University School of Electrical Engineering Chengdu611756 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Inner Mongolia Electric Power Research Institute Hohhot010020 China Department of Electrical and Computer Engineering China City University of HongKong Department of Electrical Engineering Hong Kong State Grid Sichuan Electric Power Research Institute Chengdu610041 China The Hong Kong Polytechnic University Research Institute of Smart Energy Department of Electrical and Electronic Engineering Hong Kong

The traditional model-based energy management strategy (EMS) for regenerative braking energy storage systems (RBESS) is obsoleting in the face of increasingly complex and un-certain operation conditions in railway power system (RPS). In this paper, a model-free deep reinforcement learning (DRL) method is proposed. First, the multi-objective energy manage-ment problem for RBESS is formulated to concurrently achieve the RBE utilization and power demand shaving of RPS. Then, this problem is modeled as a Markov decision process (MDP) to be solved by the DRL-based method. Specifically, the RBESS con-troller is modeled as an agent to interact with the environment modeled as the RPS integrated with RBESS. To coordinate the agent to learn the optimal strategies regarding multiple energy management objectives in different time scales, a multistage reward function involving the step reward and final reward is de-signed. Based on the above elements, the double deep Q-learning algorithm is applied to train the agent for optimizing the EMS. Finally, the proposed DRL-based EMS is tested on the OPAL-RT experimental platform by using the field load data. Case studies have demonstrated that the proposed method outperforms the traditional rule-based and optimization-based methods by over 5% in the energy management objective. © 2015 IEEE.

关键词： Deep reinforcement learning

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Chattering-Free Fault-Tolerant Cluster Control and Fault Direction Identification for HIL UAV Swarm With Pre-Specified Performance

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 183-197页

作者： Pei-Ming Liu Xiang-Gui Guo Jian-Liang Wang Daniel Coutinho Lihua Xie the Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing the Shunde Graduate School of University of Science and Technology Beijing IEEE Autonomous Intelligent Systems Department Hangzhou Innovation Institute of Beihang University the Department of Automation and Systems Universidade Federal de Santa Catarina the School of Electrical and Electronic Engineering Nanyang Technological University

In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the presence of possible nonidentical and unknown direction faults(NUDFs) in the yaw *** control strategy begins with the design of a pre-specified performance event-triggered observer for each individual *** observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer *** is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.

关键词： Chattering-free cluster consensus fault direction identification human-in-the-loop (HIL) nonidentical and unknown direction faults (NUDFs) pre-specified performance swarm unmanned aerial vehicles (UAVs)

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Broadband single-polarization single-mode low confinement loss hollow core anti-resonant fiber with semi-elliptical nested tube

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Optical and Quantum Electronics 2025年第4期57卷 1-12页

作者： Lin, Wen Fei, Yihong Wang, Ning Jia, Hongzhi Engineering Research Center of Optical Instruments and Systems Ministry of Education Shanghai Key Laboratory of Modern Optical Systems School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

In this paper, a hollow-core anti-resonant optical fibre containing a semi-elliptical nested tube is proposed, which has the characteristics of single-polarization, large bandwidth, single-mode and low confinement loss. By optimizing the structural design, the polarization extinction ratio (PER) of the fiber reaches 21,0183 at a wavelength of 1.55 μm, and the y-polarized fundamental mode loss is only 0.00086 dB/m. By changing the material and thickness of the semi-ellipsoidal nested tube, a large bandwidth of 280 nm was achieved in the wavelength range of 1.51-1.78 μm, with loss limited to less than 0.001 dB/m within the bandwidth range. The PER and higher-order mode extinction ratio of 4870, 1487, respectively. The loss remains below 0.01 dB/m when the bending radius exceeds 4.5 cm. Therefore, it is expected that this optical fiber can be used in optical devices such as fiber optic sensors, fiber optic lasers and fiber optic gyroscopes. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Single mode fibers

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Optimizing Autonomous Intersection Control Using Single Agent Reinforcement Learning 25

Optimizing Autonomous Intersection Control Using Single Agen...

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26th International Conference on Distributed Computing and Networking, ICDCN 2025

作者： Ganar, Yash Kumar, Vinay Dulera, Shraddha Yadav, Ram Narayan Electrical and Computer Science Engineering Institute of Infrastructure Technology Research and Management Ahmedabad India

ISBN: (纸本)9798400710629

Autonomous intersection management (AIM) presents significant challenges due to the complexity of real-world traffic scenarios and the reliance on a costly centralized server to manage and coordinate all vehicles simultaneously. In this work, we address the challenge of efficiently and safely navigating intersections using a Reinforcement Learning (RL). In this work, we proposed two autonomous intersection management algorithms based on (i) Proximal Policy Optimization (PPO), and (ii) Advantage Actor-Critic (A2C). We design a reward function to encourage the system to reduce collisions while maintaining high throughput. By training and testing these algorithms in complex traffic scenarios, we aim to identify which algorithm demonstrates better decision-making capabilities under different conditions. We evaluated performance across multiple metrics, including collision avoidance, safe and efficient travel speed, time to reach the destination, and reward functions. We have established a structured approach to help researchers make informed decisions regarding suitable algorithm selection. It provides a balanced comparison between the algorithms and suggests a recommendation system for intersection traffic environments, considering various performance metrics such as reward, collision, speed, and travel time. © 2025 Copyright held by the owner/author(s).

关键词： Travel time

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Automatic emotion recognition using deep neural network

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Multimedia Tools and Applications 2025年 1-30页

作者： Sujatha, R. Chatterjee, Jyotir Moy Pathy, Baibhav Hu, Yu-Chen School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of CSE Graphic Era University Dehradun India School of Electrical Engineering Vellore Institute of Technology Vellore India Department of Computer Science Tunghai University Taichung City Taiwan

Emotions are a vital semantic part of human correspondence. Emotions are significant for human correspondence as well as basic for human–computer cooperation. Viable correspondence between people is possibly achieved when both the importance and the emotion of the correspondence are perceived by all groups included. Understanding the significance of language has generally been concentrated on in natural language processing (NLP) as a semantic examination. In NLP, the text can be handled appropriately for classification. Emotion detection from facial emotion is the subfield of social signal processing applied in a wide assortment of regions, explicitly for human and PC collaboration. Many researchers have proposed various approaches, generally utilizing machine learning concepts. Automatic emotion recognition (AER) is significant for working with consistent intuitiveness between a person and a smart device toward fully acknowledging an intelligent society. Many researchers examined cross-lingual and multilingual speech emotion as a stage toward language-free emotion acknowledgment in natural speech. In the present work, we are proposing a deep learning-based AER system using four openly accessible datasets, namely Basic Arabic Vocal Emotions Dataset (BAVED), Acted Emotional Speech Dynamic Database (AESDD), Urdu written in Latin/Roman Script (URDU), and Toronto Emotional Speech Set (TESS), by utilizing the Jupyter notebook and a Python library for music and audio synthesis named Librosa. The experimental results exhibited that the proposed approach achieves better than the existing approaches, i.e., the accuracy of the proposed system with the URDU dataset is 96.24%, the TESS dataset is 99.10%, the AESDD dataset is 65.97%, and the BAVED dataset is 73.12%. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantics

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Distributed Global Nash Equilibrium of Interactive Adversarial Graphical Games

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Journal of systems Science & Complexity 2025年第2期38卷 613-632页

作者： ZHANG Yizhong LIAN Bosen LEWIS Frank L. Department of Electrical and Computer Engineering Auburn University UTA Research Institute University of Texas at Arlington

This article formulates interactive adversarial differential graphical games for synchronization control of multiagent systems(MASs) subject to adversarial inputs interacting with the systems through topology communications. Local control and interactive adversarial inputs affect each agent's local synchronization error via local networks. The distributed global Nash equilibrium(NE) solutions are guaranteed in the games by solving the optimal control input of each agent and the worst-case adversarial input based solely on local states and communications. The asymptotic stability of the local synchronization error dynamics and the NE are guaranteed. Furthermore, the authors devise a data-driven online reinforcement learning(RL) algorithm that only computes the distributed Nash control online using system trajectory data, eliminating the need for explicit system dynamics. A simulation-based example validates the game and algorithm.

关键词： Adversarial inputs differential graphical games Nash equilibrium reinforcement learning

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A Star-Connected Railway Energy Router and its Control Strategy for new Energy Integration into AC Traction Substation

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IEEE Transactions on Energy Conversion 2025年第1期40卷 371-381页

作者： Lian, Jingru Dai, Chaohua Yao, Zhigang Chen, Weirong Wang, Caisheng Southwest Jiaotong University School of Electrical Engineering Chengdu611756 China Nanyang Technological University Energy Research Institute 639798 Singapore Wayne State University Department of Electrical and Computer Engineering DetroitMI48202 United States

For back-to-back railway energy routers (BTB-RER), renewable energy utilization, regenerative braking energy (RBE) recycling, and traction inter-phase power balance are all achieved through two back-to-back (BTB) inverters, resulting in high hardware capacity requirements and system costs. This paper proposes a novel star-connected structure of an interphase-bridging inverter (IBI) and BTB inverters. This star-connected structure leverages not only the advantage of the smaller hardware rating of IBI but also the flexible controllability of BTB inverters, thereby reducing system costs while realizing similar functionality. Firstly, the power transfer principles and operational modes of the star-connected structure are analyzed to reveal the power complementarity relationship between the IBI and the BTB inverters. Subsequently, in response to the characteristics of multi-functionality and multi-directional energy flow, a power optimization control strategy is proposed to maximize the utilization of photovoltaic (PV) and RBE while enhancing power quality as much as possible. Finally, the superiority of the proposed star-connected structure is validated via hardware-in-the-loop experiments, and the measured data shows a 15% reduction in both inverter and transformer capacity requirements. © 1986-2012 IEEE.

关键词： Reactive power

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An integrated strategy of AEF attribute evaluation for reliable thunderstorm detection

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Digital Communications and Networks 2025年第1期11卷 234-245页

作者： Xu Yang Hongyan Xing Xinyuan Ji Xin Su Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada College of Internet of Things Engineering Hohai UniversityChangzhou 213022China Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye UniversitySariyer/IstanbulTurkey

Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain *** is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and *** this paper,a strategy is proposed to integrate three currently competitive WA's evaluation ***,a conventional evaluation method based on AEF statistical indicators is *** evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy *** AEF attributes contribute to a more accurate AEF classification to different *** resulting dynamic weighting applied to these attributes improves the classification *** evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation *** integration in the proposed strategy takes the form of a score *** cumulative score levels correspond to different final WA *** imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm *** results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA *** is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.

关键词： Atmospheric electric field(AEF) Thunderstorm Attribute Fuzzy c-means Imaging

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Flexible, Super-stable, and Multifunctional Capacitive Pressure Sensors with Tilted Micropillar Array by Inclined Laser Ablation and Demolding

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IEEE Sensors Journal 2025年第6期25卷 9367-9374页

作者： Xu, Tianlong Li, Kaixin Zhou, Yihao Zhang, Dawei Sheng, Bin College of Optical Electrical and Computer Engineering Unversity of Shanghai for Science and Technology Shanghai 200093 China. Shanghai Key Laboratory of Modern Optical Systems Engineering Research Center of Optical Instruments and System Shanghai 200093 China

Flexible capacitive pressure sensors have garnered considerable interest across diverse applications, including medical monitoring, electronic skin, and robotic tactile systems, owing to their straightforward fabrication process, low energy consumption, and robust stability. In this paper, we introduce a new inclined laser ablation (ILA) combined with demolding technique for the fabrication of flexible capacitive sensors featuring a microstructured dielectric layer composed of a tilted micropillar array (TMA). The design parameters of TMA were systematically optimized, including the tilt angle of the micropillars, array gap, aspect ratio, and bottom film thickness. The resulting capacitive pressure sensor, equipped with 75° tilted micropillar arrays (aspect ratio of 5:1), demonstrates exceptional sensitivity (1.12 kPa-1) within the low-pressure range (0-2 kPa), rapid response and recovery times, a low pressure detection limit of 0.25 Pa, and transient response stability factor as high as 243.9. The proposed capacitive pressure sensor was validated for the detection and recognition of human motions when attached to various body parts. Additionally, the sensors also demonstrated significant potential for diverse applications, including tactile sensing, and Morse code communication. © 2025 IEEE.

关键词： Aspect ratio

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In-band full-duplex MIMO PLC systems for relaying networks

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Digital Communications and Networks 2025年第1期11卷 145-159页

作者： Francisco J.Canete Gautham Prasad Lutz Lampe Communications and Signal Processing Lab Telecommunication Research Institute(TELMA)ETS Ingenieria TelecomunicacionUniversidad de MalagaSpain Ofinno RestonVAUSA Department of Electrical and Computer Engineering The University of British ColumbiaCanada

In Power Line Communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long ***,PLC networks often employ repeaters/relays,especially in smart grid neighborhood area *** in broadband indoor PLC systems that offer a notable data rate,relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things *** this paper,we study Multiple-Input Multiple-Output(MIMO)PLC systems that incorporate inband full-duplex functionality in relaying *** present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC *** reach this analysis,we get channel realizations from random network layouts for indoor and outdoor *** adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC *** concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput:smart grids with enhanced communications in outdoor scenarios,and“last meter”systems for high-speed connections everywhere in indoor ones.

关键词： PLC MIMO Relaying networks OFDM Spatial correlation Performance analysis

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