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Distributed Temperature Sensing Based on Chaotic Brillouin Scattering Power Measurement

IEEE Sensors Journal 2025年第9期25卷 15968-15974页

作者： Xu, Jinglang Zhang, Jianzhong Li, Jian Ma, Zhe Liu, Shuangshuang Zhang, Yubo Wang, Zhikun Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronic Engineering Taiyuan030024 China

A high-accuracy distributed temperature sensing scheme utilizing chaotic Brillouin scattering power (BSP) combined with the cross correlation measurement method was proposed and experimentally demonstrated. The proposed scheme employs the chaotic laser as the sensing signal, adopting the chaotic cross correlation positioning principle instead of the conventional optical time-domain reflection (OTDR) principle. Additionally, it combines a single-path ratio method to accurately demodulate the temperature. This positioning method uses the random amplitude characteristics of chaotic lasers in the time domain. It overcomes the limitation of pulsewidth on spatial resolution in distributed temperature sensing based on OTDR principles. And it resolves the trade-off between spatial resolution and sensing distance. Experimental results demonstrated that the spatial positioning accuracy was optimized from 5.0 to 0.43 m with a 50 ns pulsewidth modulation, achieving a sensing distance of up to 10 km. This scheme aims to achieve high spatial positioning accuracy while maintaining a long sensing distance. This is crucial for early fire warning and effective emergency response in long-distance fire monitoring applications. © 2025 IEEE.

关键词： Brillouin scattering

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Continuous Feature Representation of Fault Location Based on Electrical Distance for Generalizable Data-Driven Dynamic Security Assessment

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IEEE Transactions on Power systems 2025年

作者： Qi, Hang Li, Changgang Liu, Yutian Sun, Runjia Yan, Jiongcheng Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Jinan250061 China

Pre-fault dynamic security assessment (DSA) of power systems needs to consider different fault locations. Existing data-driven DSA methods lack generalizable fault location features, failing to accurately assess unlearned fault locations, i.e., fault locations not in the training set. To address this issue, this paper proposes a continuous feature representation method of fault location based on electrical distance, aiming to construct a pre-fault DSA model generalizable to unlearned fault locations. Firstly, fault location is represented continuously as an electrical coordinate with the electrical distance to preselected reference nodes. Then, the representation ability of electrical coordinates to fault locations is optimized by reference node selection and metric learning. Finally, with electrical coordinates and steady-state features as input, a hybrid DSA model composed of convolutional and radial basis function networks is constructed to assess system angular and voltage dynamics with different fault locations. The generalization performance of the proposed DSA method on unlearned fault locations is verified on New England 39-bus system and a provincial system of China. © 1969-2012 IEEE.

关键词： data-driven Fault location feature representation power system pre-fault dynamic security assessment

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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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Integrated dispatching Model for Power system Incorporating Multiple Modules

Integrated Dispatching Model for Power System Incorporating ...

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Advances in Electrical, Electronics and Computing Technology (EECT), International Conference on

作者： Chang Xu Mingqiang Wang Zihan Wang Yizhe Zhang Jialiang Wang Fengbin Sun Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

The widespread integration of renewable energy presents significant challenges for power system scheduling. Traditional power system scheduling is mainly based on the concept of “coordinating on a multi-time-level and gradually refining at each level,” using a sequential scheduling framework. However, with the growing integration of renewable energy, the uncertainty in power systems has significantly increased, leading to severe issues such as conflicts in the coordination between different modules. This paper first introduces the scheduling framework of the traditional sequential scheduling model. Then, addressing the problems of module coordination and insufficient flexibility, an integrated multi-time-scale scheduling model is proposed. This model combines day-ahead and intraday scheduling models, optimizing decision variables including unit start/shut states, operation points, and reserves simultaneously to maximize the collaborative potential between different scheduling modules. After linearization, the proposed model is converted into a mixed-integer linear programming (MILP) model, which can be solved directly using commercial optimization solvers. Finally, case analyses demonstrate the effectiveness and superiority of the proposed integrated model compared to the traditional sequential scheduling model.

关键词： Renewable energy sources Analytical models Uncertainty Fluctuations Processor scheduling Refining Regulation Power systems Power system reliability Load modeling

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Optimal Scheduling Considering Multiple Reserves Based on Active Power Curtailment Operation of Wind Power

Optimal Scheduling Considering Multiple Reserves Based on Ac...

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Advances in Electrical, Electronics and Computing Technology (EECT), International Conference on

作者： Zihan Wang Mingqiang Wang Chang Xu Jialiang Wang Yizhe Zhang Caishuai Liang Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

Under the current general trend of the power industry's transformation towards clean energy, wind power generation, as an important form of renewable energy utilization, is steadily increasing its proportion in the power system. However, the inherent volatility and uncertainty of wind power bring numerous challenges to the stable operation of the power system. Firstly, based on the traditional unit commitment model, this paper comprehensively considers the capacity reserve and ramping reserve of the power system, and constructs a unit commitment model that considers the supply and demand constraints of both types of reserves simultaneously. Then, on the basis of this model, an in-depth and comprehensive discussion is carried out, focusing on the key operation strategy of the active power curtailment operation of wind power. This not only helps to improve the power system's ability to accommodate wind power, but also enables a better response to the challenges of volatility and uncertainty brought by wind power to the power system, thus ensuring the safe, stable and economic operation of the power system. Finally, the model is transformed into a mixed-integer linear programming model that can be directly called by the commercial solver CPLEX, and the effectiveness of the model is verified by a modified IEEE 26-node distribution network.

关键词： Uncertainty Fluctuations Costs Supply and demand Power supplies Wind power generation Power system stability Stability analysis Power system reliability Wind turbines

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Robust Consensus Based Secondary control for Microgrids Considering Communication Delay and Noises: A Kalman Filter Based Approach

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IEEE Transactions on Smart Grid 2025年

作者： Zhao, Qi Zhang, Wen Zhang, Tingting Chen, Jian Ye, Hua Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Jinan250061 China Shandong University Shandong Research Institute of Industrial Technology Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Jinan250061 China

To achieve the frequency and voltage regulation as well as active and reactive power sharing, the consensus-based secondary controls of microgrids rely on communication network to exchange signals between neighbor inverters, which may be affected by the communication delay and noises. Unlike the existing methods that focus solely on communication delay, this paper proposes a Kalman filter-based robust consensus control to address the communication delay and noises comprehensively. Based on the discrete differential equation of the signal transmitted via communication network, the multi-step prediction model of the delayed signal is firstly built by considering the prediction errors. The state space model is then constructed by taking the predicted signals at each step as the state variables while the delayed and noise-involved signal and its differential value are seen as the measurements. A Kalman filter is further designed to comprehensively handle the communication delay, noises and prediction errors to estimate the true signal generated from neighbor inverters. With the estimated signals of all neighbor inverters, the consensus control is performed to coordinate the grid-following and grid-forming inverters within the microgrid. The effectiveness of the proposed method is demonstrated with simulations and experiments performed on the modified IEEE-33 bus-based microgrid. © 2010-2012 IEEE.

关键词： Kalman filters

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Optimized Gaussian kernel regression for X-ray pulsar signal profile construction 3

Optimized Gaussian kernel regression for X-ray pulsar signal...

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3rd International Conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2024

作者： Dong, Yan Zhuang, Yutao Wang, Ruoning National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing 100071 China

ISBN: (纸本)9781510690219

With the continuous advancement of pulsar-based navigation technology, signal processing issues in X-ray pulsar navigation applications have received increasing attention. One of the key factors limiting the improvement of navigation accuracy is the low signal-to-noise ratio (SNR) of epoch-folded profiles. Pulsar profiles contain many important characteristic features, such as pulse shape symmetry and multi-pulse structures. To facilitate further study, it is necessary to reduce noise and obtain high-SNR pulsar profiles. This study addresses this issue by proposing a method for high-precision pulsar profile construction based on optimized Gaussian kernel regression. The constructed profiles are evaluated and analyzed in terms of profile quality and phase information estimation based on the profile. The results show that the SNR of the epoch-folded profiles after denoising is significantly better than that of the original profiles, providing an important reference for signal processing in X-ray pulsar navigation applications. © 2025 SPIE.

关键词： Gaussian Kernel Regression Pulsar Photon Time Series Pulse Profile Signal Denoising

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Coprime Factorization-Based Encryption and Attack Detection for Nonlinear Cyber-Physical systems Using Deep Learning Approach

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 14020-14029页

作者： Wu, Shimeng Luo, Hao Zhang, Jiusi Qiao, Xinyu Tian, Jilun Jiang, Yuchen Harbin Institute of Technology Department of Control and Simulation Center Harbin150001 China National Key Laboratory ofComplex System Control and Intelligent Agent Cooperation Harbin150001 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper presents a data-driven framework for integrating encryption transmission and attack detection in cyber-physical systems (CPS) with nonlinear physical plants. The main focus of this research is to use deep neural networks to realize the coprime factorization (CF) of nonlinear systems. The definition of the CF guides the network training and designing process, and the model’s topology is designed in the state-space form, which improves the interpretability of the data-driven CF. Based on the CF-aided neural networks, an encrypted transmission module is designed that projects information related to system dynamics into a perpendicular data space, which complements existing encryption methods from a control theory perspective. Subsequently, an anomaly detector are designed using the same CF pairs. This detector not only provides high-accuracy detection of attacks but also distinguishes between attacks and faults, thereby reducing the false positive rate and enhancing the reliability of the attack detection. The proposed method has been validated in a real CPS using a mecanum-wheeled vehicle as the physical plant, demonstrating its effectiveness and applicability. © 2004-2012 IEEE.

关键词： Factorization

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Bandwidth enhancement and the flattening of a chaotic laser with a microring resonator

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Optics Express 2025年第9期33卷 19535-19545页

作者： Guo, Zhi-Yong Li, Jian-Cheng Qiao, Li-Jun Wei, Xiao-Jing Zhang, Ming-Jiang College of Physics and Optoelectronic Engineering Taiyuan University of Technology Taiyuan030024 China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China Shanxi Key Laboratory of Precision Measurement Physics Taiyuan University of Technology Taiyuan030024 China

We propose and experimentally demonstrate what we believe to be a novel scheme for bandwidth enhancement and flattening of a chaotic laser with a microring resonator. By leveraging the multi-beam interference effect within the MRR, the multiple chaotic laser exhibited improved bandwidth and power spectrum flatness. With a feedback strength of 6 and a laser bias current of 11.8 mA, the chaotic laser with a power spectrum that extends to 22.65 GHz within -3 dB is experimentally achieved. Additionally, we investigated the impact of the different feedback strengths and bias currents on the bandwidth and flatness of the chaotic laser. Finally, we investigated the correlation between the two channels, which can produce single-channel chaotic lasers with correlations below 0.25 over a wide range. This method offers promising chaotic light sources for applications in chaotic distributed fiber optic sensing, secure communication, and chaotic LIDARs. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Bandwidth

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A Seamless Pedestrian Localization system Based on GNSS/IμUWB/MAP Integration

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IEEE Internet of Things Journal 2025年第11期12卷 16653-16667页

作者： Zhang, Shuning Tang, Hongjing Chen, Liangming Gao, Yufeng Southern University of Science and Technology School of Automation and Intelligent Manufacturing Shenzhen518055 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China Beijing Institute of Spacecraft System Engineering Beijing100094 China

Pedestrian localization has broad applications. However, achieving seamless positioning in complex environments remains a significant challenge due to factors like environmental occlusion and indoor-outdoor transitions. This paper proposes a combined localization framework using Global Navigation Satellite system (GNSS), Inertial Measurement Unit (IMU), Ultra-Wideband (UWB), and MAP data to address this issue. In the framework, a three-step GNSS localization method is proposed to enhance accuracy and stability by eliminating Non-Line-of-Sight (NLOS) effects and filtering anomalies. Inertial Navigation system (INS) and Pedestrian Dead Reckoning (PDR) models are integrated to improve local precision and stability. UWB, known for its superior localization capabilities, has been integrated into some smartphones and is promising for large-scale indoor applications. The paper presents a gradient descent-based optimal anchor deployment algorithm and localization methods for varying anchor quantities. Additionally, a non-stationary Markov model fuses map data for trajectory prediction and correction. Finally, anomaly detection filtering and low-pass filtering are applied to the corrected trajectories, yielding high accuracy and stability. Experiments on the Honor V20 and iQOO U3 smartphones showed significant improvements compared to the baseline algorithm. Outdoor Root Mean Square Error (RMSE) was reduced by 44.4% (10.83m) for the Honor V20 and 40.0% (10.77m) for the iQOO U3. Additionally, outdoor Standard Deviation (STD) improved by 43.9% (4.80m) and 43.5% (5.50m), respectively. In transitional areas, RMSE improved by 4.61% (10.77m) and 19.6% (4.76m), respectively. Indoor RMSE also showed improvements, with the Honor V20 reducing it by 8.00% (3.79m) and the iQOO U3 by 5.78% (3.91m). © 2025 IEEE.

关键词： Location awareness Global navigation satellite system Accuracy Pedestrians Filtering Sensors Prediction algorithms Predictive models Smart phones Kalman filters

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