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Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

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Neural Regeneration Research 2025年第9期20卷 2520-2537页

作者： Chonglin Su Taiqi Huang Meiyu Zhang Yanyu Zhang Yan Zeng Xingxing Chen Brain Science and Advanced Technology Institute Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of MedicineWuhan University of Science and TechnologyWuhanHubei ProvinceChina

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental *** the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and *** glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic *** interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive *** appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive *** with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor *** review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive *** emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive *** provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.

关键词： brain-derived neurotrophic factor calcium signaling glucocorticoid receptor glucocorticoid glutamate transmission hypothalamic-pituitary-adrenal axis long-term potentiation neurocognitive disorders neuroplasticity stress

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Time-varying formation-containment control for heterogeneous multi-agent systems with communication and output delays via observer-based feedback protocol

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15435-15448页

作者： Yang, Yi He, Yong China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

In this article, the time-varying formation-containment control problem of heterogeneous multi-agent systems (MASs) with an observer-based state feedback protocol is studied, where both communication delays and output delays are taken into consideration. By introducing an augmented Lyapunov-Krasovskii functionals (LKFs) candidate and employing less conservative methods to estimate its derivative, an improved quasi-formation-containment criterion is derived. On this basis, some observers and controllers are designed to allow for a larger maximum upper bound (MUB) of time delays on the premise of guaranteeing the fulfillment of the time-varying formation of leaders and the bounded convergence of followers. The estimation of the MUB determines the allowable delay range for system stability under the designed observers and controllers. Moreover, a distributed algorithm is developed to calculate the MUB of time delays, the observer gains, and the controller gains. Finally, two simulation experiments are implemented to demonstrate the obtained results, which verify the superiority and practicability of the criterion and algorithm. © 2004-2012 IEEE.

关键词： State feedback

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D-FUSION SLAM: A VSLAM SYSTEM OPTIMIZED BY INTEGRATING DEPTH INFORMATION AND RGBD FEATURE POINTS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2025年第1期87卷 121-138页

作者： Zheng, Qingchun Wu, Moudong Zhu, Peihao Yang, Bin Li, Shubo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China

This paper introduces D-Fusion SLAM, an advanced VSLAM system based on ORB-SLAM2. D-Fusion SLAM integrates depth information to enhance feature selection, aiming to improve accuracy and speed in visual SLAM applications. The system mainly comprises two modules: an image grid filtering module based on grayscale information and a feature selection module integrating depth information. These modules effectively eliminate redundant and useless features, ensuring high-quality features for pose estimation. We tested D-Fusion SLAM on the TUM dataset and compared it with ORB-SLAM2. Experimental results demonstrate that D-Fusion SLAM outperforms ORB-SLAM2, significantly enhancing the system's accuracy and robustness. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Feature Selection

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Spatial confinement of free-standing graphene sponge enables excellent stability of conversion-type Fe_(2)O_(3)anode for sodium storage

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Chinese Chemical Letters 2025年第3期36卷 544-549页

作者： Jun Dong Senyuan Tan Sunbin Yang Yalong Jiang Ruxing Wang Jian Ao Zilun Chen Chaohai Zhang Qinyou An Xiaoxing Zhang Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Nanjing University of Aeronautics and Astronautics Nanjing 210016China

Conversion-type anode materials are highly desirable for Na-ion batteries(NIBs)due to their high theoretical ***,the active materials undergo severe expansion and pulverization during the sodiation,resulting in inferior cycling ***,a self-supporting three-dimensional(3D)graphene sponge decorated with Fe_(2)O_(3)nanocubes(rGO@Fe_(2)O_(3))is ***,the 3D graphene sponge with resilience and high porosity benefits to accommodate the volume expansion of the Fe_(2)O_(3)nanocubes and facilitates the rapid electrons/ions transport,enabling spatial confinement to achieve outstanding ***,the free-standing rGO@Fe_(2)O_(3)can be directly used as an electrode without additional binders and conductive additives,which helps to obtain a higher energy *** on the total mass of the rGO@Fe_(2)O_(3)material,the rGO@Fe_(2)O_(3)anode presents a specific capacity of 859 mAh/g at 0.1 A/*** also delivers an impressive cycling performance(327 mAh/g after 2000 cycles at 1 A/g)and a superior rate capacity(162mAh/g at 20 A/g).The coin-type Na_(3)V_(2)(PO_(4))_(3)@C//rGO@Fe_(2)O_(3)NIB exhibits an energy density of 265.3Wh/*** unique 3D ionic/electronic conductive network may provide new strategies to design advanced conversion-type anode materials for high-performance NIBs.

关键词： Conversion-type anode Spatial confinement Fe_(2)O_(3) Graphene network Self-supporting Sodium-ion batteries

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent Systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Prediction of transmission spectrum from photonic energy band via autoencoder network

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IEEE Photonics Technology Letters 2025年第13期37卷 737-740页

作者： Mo, Wenqin Zhu, Yaling Yin, Yuanxing Dong, Kaifeng Jin, Fang Song, Junlei China University of Geosciences School of Automation Wuhan430074 China China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Optical topological insulators, as an emerging type of photonic material, present substantial benefits for optical communication. The advanced pattern recognition capabilities of deep learning have propelled the inverse design of topological photonic structures into a hot area of research. However, existing methods encounter difficulties with the analysis of intricate band structures. Therefore, we construct a deep learning model capable of handling two-dimensional data of photonic energy band. Utilizing an autoencoder network, our model indirectly trains the photonic energy band and transmission spectrum, by converting them into feature coding. It integrates a transmission spectrum autoencoder and a photonic energy band autoencoder, processing energy band data to predict the corresponding transmission spectrum. The results indicate that compared to convolutional neural network (CNN), our model can accurately predict transmission spectrum, and perform better on both evaluation metrics of RMSE and R2. This work enhances prediction accuracy by leveraging energy band diagrams to constrain optical properties. © 1989-2012 IEEE.

关键词： Topological insulators

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Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University the National Key Laboratory of Continental Shale Oil of China Northeast Petroleum University the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

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Research on Urban Air Quality Prediction Method Based on the Fusion of Wide-area Spatiotemporal Distribution Data 26

Research on Urban Air Quality Prediction Method Based on the...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Tao, Zixing Cao, Weihua Gan, Chao Wuhan China School of Future Technology School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9798331521950

Air quality data exhibit nonlinearity, sensitivity to environmental factors, and long-term dependencies. Numerous factors influence air quality, making accurate predictions based on a single-dimensional dataset impractical. This study proposes a method for urban air quality prediction that integrates wide-area spatiotemporal data, designed to address the unique characteristics of air quality datasets. First, relevant wide-area spatiotemporal data are selected, and their correlations with air quality are systematically analyzed. Second, a Long Short-Term Memory (LSTM) network-based Transformer model is utilized to capture the long-term dependencies in the air quality sequences. Finally, the model successfully generates hourly multi-step predictions for six air pollutants. The experimental results show that the proposed method outperforms the method that relies on air quality data alone for multi-step air quality prediction. © 2025 IEEE.

关键词： Air quality

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