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Achieving the Social Optimum in a Nonconvex Cooperative Aggregative Game: A Distributed Stochastic Annealing Approach

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IEEE Transactions on Neural Networks and Learning Systems 2025年第5期36卷 9709-9716页

作者： Wang, Yinghui Geng, Xiaoxue Chen, Guanpu Zhao, Wenxiao University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China Yunnan Normal University School of Mathematics Yunnan Key Laboratory of Modern Analytical Mathematics and Applications Kunming650500 China KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm100 44 Sweden Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing100049 China

This brief designs a distributed stochastic annealing algorithm for nonconvex cooperative aggregative games, whose players’ cost functions not only depend on players’ own decision variables but also rely on the sum of players’ decision variables. To seek the social optimum of cooperative aggregative games, a distributed stochastic annealing algorithm is proposed, where the local cost functions are nonconvex and the communication topology between players is time-varying. The weak convergence to the social optimum of the algorithm is further analyzed. A numerical example is finally given to illustrate the effectiveness of the proposed algorithm. © 2012 IEEE.

关键词： Cost functions

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Location of Subsynchronous Oscillation Source in Power Systems Using Multivariate Synchrosqueezing Generalized S-Transform

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Dianli Xitong Zidonghua/Automation of Electric Power Systems 2025年第9期49卷 135-145页

作者： Jiang, Tao Zhang, Peng Li, Xue Liu, Bohan Li, Guoqing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

Fast and accurate location of subsynchronous oscillation source is of great significance to the secure and stable operation of power system. The existing location methods for subsynchronous oscillation source are difficult to be applied to multi-mode time-varying subsynchronous oscillation scenarios, and the computational efficiency needs to be improved. Therefore, a location method for subsynchronous oscillation source in power systems using multivariate synchrosqueezing generalized S-transform (MSSGST) is proposed. First, the energy ratio coefficient is calculated in the adaptive sliding time window to detect the subsynchronous oscillation phenomenon in real time. For the detected subsynchronous oscillation phenomenon, the joint measurement information matrix is constructed with nodes as the unit, and the joint time-frequency matrix is obtained by synchronous decomposition of the joint measurement information matrix using MSSGST. Then, the MSSGST coefficient matrix, which can characterize the subsynchronous oscillation mode of the system, is screened and reassembled by ridge extraction technique. On this basis, the time-frequency domain transient energy flow calculation model based on MSSGST is derived, and the location index of oscillation source is constructed according to the energy characteristics in time-frequency domain during subsynchronous oscillation. Finally, the accuracy and effectiveness of the proposed method are verified by simulation data and measured data of subsynchronous oscillation of the actual power grid. © 2025 Automation of Electric Power Systems Press. All rights reserved.

关键词： Electric power transmission networks

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Non-contact all-optic OCT–PAM imaging with shared detection light

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Applied Optics 2025年第13期64卷 3431-3437页

作者： Ding, Ning Xiang, Ben Jiang, Huiwen Yue, Jinyun Yu, Yao Liu, Jian Zhao, Yuqian Luan, Jingmin Yang, Yanqiu Wang, Yi Ma, Zhenhe College of Information Science and Engineering Northeastern University Shenyang 110819 China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao 066004 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao 066004 China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao 066004 China

We proposed a non-contact all-optic OCT–PAM dual-modal system based on a single detection light source. A homodyne low-coherence interferometer was adopted to detect the vibration induced by photoacoustic excitation. The optical coherence tomography (OCT) and photoacoustic microscopy (PAM) shared the same broadband light source for signal detection, thus simplifying the dual-modal system and making it compact. Using the proposed system, we performed absorption-scattering imaging of human hairs, measured the femoral artery and vein flow rates in mice, and imaged the auricle blood vessels in mice in vivo. The combination of OCT and PAM can provide complementary biological tissue information and offer a richer reference for the diagnosis of diseases. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Biomedical imaging Fabry Perot interferometers Imaging systems Imaging techniques Optical imaging Tissue imaging

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Moving-Window Integrated Physics-Data-Based Modeling of Four-Wheel Vehicle Lateral Dynamics

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Automotive Innovation 2025年 1-11页

作者： Wei, Wenpeng Wang, Jinxiang Pi, Dawei Zhuang, Weichao He, Tianyi Yin, Guodong School of Mechanical Engineering Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Safety and Intelligence of Vehicle Equipment Research Center Nanjing University of Science and Technology Nanjing China Department of Mechanical and Aerospace Engineering Utah State University Logan USA

This paper presents an Integrated physics-data-based (IPDB) modeling of lateral vehicle dynamics with moving-window data snapshots. The IPDB model encodes the fundamental physical principle of four-wheel vehicle motions and simultaneously carries out the adaptiveness of the data-driven approach. Specifically, the traditional physics-based lateral dynamics considering four-wheel interaction are first derived into an affine linear-parameter-varying model, in which the vehicle-related parameters and motion variables are separated. Then, by using the Kronecker product, the IPDB model, directly formulated by the data snapshots in the moving-window fashion, is obtained for system representation. As a result, the IPDB technique rendered model is physically interpretable. The impacts of moving window length on modeling performance are numerically studied. The IPDB model accuracy is validated with data from CarSim simulations and experiments with passenger vehicles under various scenarios. It is further demonstrated that the proposed IPDB model is more data-efficient than other data-driven methods since it only uses the data snapshot in the moving window to update the model recursively. This characteristic enables the IPDB method with online modeling capability to adapt to varying driving scenarios.

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Retired Lithium-ion Batteries Screening Based on Partial Discharge Curves and an Improved Crossformer

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IEEE Transactions on Transportation Electrification 2025年

作者： Lin, Mingqiang Xu, Zijun Zheng, Gengfeng Meng, Jinhao Wang, Wei Wu, Ji Fujian Key Laboratory of Special Intelligent Equipment Safety Measurement and Control Fuzhou350003 China Chinese Academy of Sciences Quanzhou Institute of Equipment Manufacturing Fujian Institute of Research on the Structure of Matter Fujian Jinjiang362200 China Fujian Special Equipment Inspection and Research Institute Fuzhou350008 China Fujian Key Laboratory of Special Intelligent Equipment Safety Measurement and Control China Xi’an Jiaotong University School of Electrical Engineering Xi’an710049 China Xi’an Jiaotong University School of Management Xi’an710049 China Hefei University of Technology School of Automotive and Transportation Engineering Anhui Hefei230009 China

With the increasing number of retired lithium-ion batteries from electric vehicles, effective screening and classification are necessary to enable their secondary utilization. The existing retired lithium-ion battery screening methods have limitations in accuracy and high energy consumption. This paper proposes a method based on local discharge curves and an improved Crossformer model to reduce energy consumption and improve screening accuracy. Considering the actual conditions of retired lithium-ion batteries, features are extracted from the discharging stage. Select the segments of the capacity sequence that exhibit the most significant variation with the voltage sequence and construct a partial capacity-voltage sequence. The standard deviation and Shannon entropy of the capacity sequence, as well as the variance, energy, and the maximum amplitude of the low-frequency part of the Fourier-transformed voltage sequence, are used as features. Then, the Crossformer utilizes a flexible embedding mechanism and a hierarchical structure for handling the dependencies of the feature. The Crossformer is improved for classification by adding a cross-attention layer at the final stage of the Crossformer decoder, which enhances its ability to capture the dependencies between features and improves the model’s performance in battery screening classification. Finally, the validation of 252 retired batteries shows that the method achieves a classification accuracy of 94.74%, outperforming other advanced models, including the original Crossformer, Transformer, ResNet, and MLP models. © 2015 IEEE.

关键词： Lithium-ion batteries

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EAVFormer: an end-to-end audio and visual emotion recognition network based on transformers

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Multimedia Systems 2025年第3期31卷 1-22页

作者： Liu, Haoran Sun, Zijian Li, Haibin Li, Yaqian Zhang, Wenming Song, Tao School of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province Yanshan University Qinhuangdao China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Shenzhen Research Institute of Yanshan University Shenzhen China Key Lab of Measurement Technology & Instrumentation of Hebei Province School of Electrical Engineering Yanshan University Qinhuangdao China

Audio-visual emotion recognition, integrating information from various sources, enhances the comprehensive understanding and analysis of human emotions. However, existing methods in this field primarily focus on feature fusion, often overlooking the equally crucial stage of feature extraction. Typically, these methods employ pre-trained models to extract features during the initial phase, complicating modality-specific feature extraction and increasing system complexity and coordination challenges, which hinder effective audio-visual feature fusion. To address these issues, we propose an end-to-end audio-visual emotion recognition model, EAVFormer. For the audio modality, we input raw audio signals along with a mix of mel spectrograms and Mel Frequency Cepstral Coefficients (MFCCs), employing a hierarchical transformer technique that facilitates both shallow local and deep global feature extraction to fully harness complementary acoustic information, significantly enhancing the acoustic modality’s contribution. For the visual modality, we input raw video frames and employ a hierarchical transformer feature extraction method that integrates three-dimensional convolution and spatio-temporal self-attention mechanisms to address spatial and temporal redundancies and dependencies, thereby enhancing the expression of dynamic visual information. In the modal fusion stage, we construct dual-modality representations and encode inter-modal information while preserving modality-specific and meaningful intra-modal features. Testing on three popular datasets RAVDESS, CREMA-D, and CMU-MOSEI demonstrates that EAVFormer surpasses existing state-of-the-art methods in audio-visual emotion recognition accuracy, achieving rates of 95.17%, 86.13%, and 78.22%, respectively.

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Node-Decomposition Privacy-Preserving for Finite-Time Secondary control of DC Microgrids

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IEEE Transactions on Smart Grid 2025年

作者： Wu, Han Zhu, Si-Min Chai, Li Zhu, Zhen-Hua Tian, Yu-Chu Wuhan University of Science and Technology Engineering Research Center of Metallurgical Automation and Measurement Technology School of Artificial Intelligence and Automation Wuhan430081 China Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou China Queensland University of Technology School of Computer Science BrisbaneQLD4001 Australia

In the distributed secondary control of DC microgrids, achieving both rapid convergence and robust information security is critical for enhancing control performance and maintaining power quality. However, current privacy-preserving approaches often compromise either control performance or privacy preservation performance. To address this challenge, this paper presents a node-decomposition privacy-preserving (NDPP) method for fully distributed, finite-time secondary control in DC microgrids. By splitting each node in the communication graph into multiple sub-nodes, the method enhances both convergence speed and privacy preservation without sacrificing control accuracy. Sub-nodes communicate within groups, and the topology of the generated graph is concealed from malicious nodes and eavesdroppers. Theoretical analysis is provided to prove finite-time voltage regulation and current sharing with privacy preservation against malicious nodes and external eavesdroppers. Simulations are conducted to verify the effectiveness of the method in maintaining control performance and power quality. © 2010-2012 IEEE.

关键词： Privacy by design

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Graphene/Epoxy Coating with Radiation Heat Dissipation Properties for Spacecraft Thermal Management

SSRN

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SSRN 2025年

作者： Li, Ning Yibo, Zhang Li, Jing Xu, Yawei School of Chemistry and Chemical Engineering South China University of Technology Guangzhou510641 China National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System Engineering Beijing100086 China South China University of Technology Zhuhai Institute of Modern Industrial Innovation Zhuhai519000 China

In the space environment, the heat dissipation of spacecraft primarily relies on thermal radiation. To reduce the weight of spacecraft, it is necessary to replace the existing copper radiators with aluminum ones. However, aluminum radiators have a lower emissivity, which results in suboptimal heat dissipation performance. Therefore, enhancing the emissivity of aluminum radiators is crucial for improving their heat dissipation performance. This study investigates the rapid (100 s) reduction of graphene oxide (GO) into low-defect reduced graphene oxide (mRGO) using Joule heating for 100 seconds, followed by non-covalent modification to further enhance its dispersion in water. By incorporating modified reduced graphene oxide (mRGO) as the primary filler in an aqueous epoxy resin emulsion and using 3-aminopropyltriethoxysilane (APTES) to enhance the adhesion between the coating and the aluminum substrate, a composite Graphene/Epoxy radiation heat dissipation coating (GERC) with high emissivity and strong adhesion was successfully prepared. Experimental results demonstrate that the coating containing 4 wt% mRGO filler exhibits the optimal heat dissipation efficiency (24.15%) and significantly enhances the infrared emissivity of the substrate (up to 0.93). This coating exhibits excellent thermal stability and strong adhesion, providing a novel approach for thermal management in space radiators. © 2025, The Authors. All rights reserved.

关键词： Aluminum coatings

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Inversion of airborne tipper and ground-based data for two-dimensional radio-magnetotelluric using the Gauss-Newton method

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Journal of Applied Geophysics 2025年 239卷

作者： Yi, Ke Zhang, Zhiyong Zhou, Feng Li, Man Wan, Jianhua Huang, Lei Deng, Hongze School of Geophysics and Measurement-control Technology East China University of Technology Nanchang330013 China Institute of Geophysics and Geomatics China University of Geosciences Wuhan430074 China Key Laboratory of Airborne Geophysics and Remote Sensing Geology Ministry of Natural Resources Beijing100083 China CGNPC Uranium Resources Co. Ltd. Beijing100029 China

A two-dimensional inversion algorithm based on the Gauss-Newton optimization has been developed for both ground-based and airborne data of Radio-magnetotelluric (RMT). The Finite Element Method (FEM) has been used in the forward modelling of RMT based on the unstructured mesh. The ground-based responses of a synthetic model including apparent resistivity, phase and tipper have been inverted and the lateral resolution of tipper has been evaluated. Then the effect of observed altitude, topography, and noise level on the airborne RMT tipper response and inverted model has been evaluated. Finally, the simultaneous inversion of ground-based data and airborne tipper has been carried out. The synthetic examples indicate that the inversion incorporating tipper data can more distinctly identify lateral resistivity variation in geological structures. The available anomaly included in the airborne tipper caused by the target structure diminishes as observed altitude increases. And the effect of topography on airborne tipper cannot be ignored, which can be eliminated by inversion with topographic consideration. When adequate airborne tipper data can be acquired, a small number of ground-based impedance data is need to be measured for obtaining resistivity values. The combined strategy of dense airborne tipper with sparse ground-based impedance measurement makes the exploration more effective and keeps great reliability for electrical resistivity imaging. © 2025 Elsevier B.V.

关键词： Magnetotellurics

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Joule Heating-Synthesized Graphene/Epoxy Radiation Heat Dissipation Coating for Spacecraft Thermal Management

SSRN

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SSRN 2025年

作者： Li, Ning Yibo, Zhang Xu, Yawei Li, Jing School of Chemistry and Chemical Engineering South China University of Technology Guangzhou510641 China National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System Engineering Beijing100086 China South China University of Technology Zhuhai Institute of Modern Industrial Innovation Zhuhai519000 China

In the space environment, the heat dissipation of spacecraft primarily relies on thermal radiation. To reduce the weight of spacecraft, it is necessary to replace the existing copper radiators with aluminum ones. However, aluminum radiators have a lower emissivity, which results in suboptimal heat dissipation performance. Therefore, enhancing the emissivity of aluminum radiators is crucial for improving their heat dissipation performance. This study investigates the rapid (100 s) reduction of graphene oxide (GO) into low-defect reduced graphene oxide (mRGO) using Joule heating for 100 seconds, followed by non-covalent modification to further enhance its dispersion in water. By incorporating modified reduced graphene oxide (mRGO) as the primary filler in an aqueous epoxy resin emulsion and using 3-aminopropyltriethoxysilane (APTES) to enhance the adhesion between the coating and the aluminum substrate, a composite Graphene/Epoxy coating (GEC) with high emissivity and strong adhesion was successfully prepared. Experimental results demonstrate that the coating containing 4 wt% mRGO filler exhibits the optimal heat dissipation efficiency (24.15%) and significantly enhances the infrared emissivity of the substrate (up to 0.93). This coating exhibits excellent thermal stability and strong adhesion, providing a novel approach for thermal management in space radiators. © 2025, The Authors. All rights reserved.

关键词： Aluminum coatings

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