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Universal Delayed Kalman Filter with Measurement Weighted Summation for the Linear Time Invariant System

Chinese Journal of Electronics 2023年第1期20卷 67-72页

作者： Quanbo Ge Tingliang Xu Xiaoliang Feng Chenglin Wen State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Institute of Information and Control Hangzhou Dianzi University Hangzhou China College of Computer and Information Hohai University Nanjing China

This paper considers the design of universal delayed Kalman filter for the networked tracking system with arbitrary random delay. Firstly, an equivalent Weighted summation form of the conventional Kalman filter (WSFKF) is given to provide a novel frame to more effectively solve the delayed filtering or Out-of-sequence measurements (OOSMs) estimate. In nature, this form makes perfectly use of the properties of offline parameters computation for Kalman filter and weighted summation of initial state estimate and the ordered measurements, which are respectively from Linear time invariant (LTI) system and Linear minimum mean square error (LMMSE) estimator. Secondly, by combing a replacement with global measurement prediction and a compensation operation based on the innovation of delayed measurement and adaptive online weighted coefficient matrix, a novel universal delayed Kalman filter which is applicable to the arbitrary random delay is designed under the WSFKF frame. Compared with the current delayed filters or OOSMs update methods, the proposed delayed estimator has not only more concise algorithm structure and better estimate accuracy but also stronger application range. The example is demonstrated to validate the proposed delayed estimator in this paper.

关键词： Weight measurement Linear systems Technological innovation Correlation Filtering Current measurement Mean square error methods

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Simultaneous Estimation of Human Motion Intention and Time-Varying Arm Stiffness for Enhanced Human-Robot Interaction

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IEEE Transactions on Cognitive and Developmental systems 2024年第3期17卷 510-524页

作者： Wu, Huayang Zhu, Chengzhi Cheng, Long Yang, Chenguang Li, Yanan University of Sussex Department of Engineering and Design BrightonBN1 9RH United Kingdom South China University of Technology Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering Guangzhou510640 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Liverpool Department of Computer Science LiverpoolL69 3BX United Kingdom

Recent advances in physiological human motor control research indicate that human endpoint stiffness magnitude increases linearly with grasp force. Based on these findings, a scheme was proposed in this paper to integrate the linear quadratic estimation (LQE) filter with the stiffness model inferred from grasp force, which can simultaneously estimate the human arm's stiffness and motion intention. Then, an online variable impedance controller (VIC) was designed based on previous estimations for physical human-robot interaction (pHRI). The proposed stiffness model and estimation method were validated through experiments using a planar robotic interface. In order to assess its performance in practical pHRI tasks, the implementation of human arm stiffness and intention estimation combining with VIC was extended to a teleoperation peg-in-hole and robot-assisted rehabilitation tasks. The experimental results demonstrate that the proposed method can effectively estimate human motion intention and arm stiffness simultaneously. Compared to existing methods, the proposed VIC enhances pHRI in terms of increased flexibility, effective guidance, and reduced human effort. © 2016 IEEE.

关键词： Human robot interaction

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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第42届中国控制会议

作者： Malak Abid Ali Khan Hongbin Ma Ying Jin Jingxiang Ma Zia Ur Rehman Mizanur Rahman School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

Deforestation is the primary source of global warming;traditional shelf labels use paper to display the price of the products,and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its *** technologies provide connectivity and a fast-updating system to eliminate the paper-based *** is one of the contenders to design the system for electronic shelf labels(ESLs).In this paper,LoRa has been used to minify data losses and guarantee the successful decoding of the carrier *** data parallelism at the network server(NS) is used to distribute the data packets among the gateways(GWs) for concurrent transmissions to the end devices(EDs).The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and *** data rate(DR) and spreading factors(SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated *** orthogonality principles follow industrial,scientific,and medical regulations(ISM) to avoid data traffic *** under different duty cycles(DC) and bandwidth(BW) are examined to minify the network saturation and reduce the energy harvesting of the tags.

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Nonlinear E-field Simulation of HVDC Converter Transformer Busing and Its Structure Optimization With RBF Neural Network and NSGA-II Algorithm 13

Nonlinear E-field Simulation of HVDC Converter Transformer B...

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13th International Conference on Power and Energy systems, ICPES 2023

作者： He, Yongsheng Zhang, Shiling Lu, Zongxiang Wang, Pengbo State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Haidian China Transmission Equipment and System Security and New Technology Dept Name of State Key Laboratory of Power Chongqing China

ISBN: (纸本)9798350345063

Static DC and PR are typical operation conditions of HVDC converter transformer bushing outlet device, moreover, the electrical parameters of RIP, transformer oil and OIP have the nonlinear relationship with E-field stress and temperature. Under the temperature gradient, the electrical parameters will modify the static DC and PR E-field distribution of the composite insulation. In order to simulate static DC and PR electric field of the composite insulation structure, this paper established the full model of the converter transformer outlet. Then, the structure parameters of converter transformer outlet have been optimized using combined RBF neural network and NSGA-II algorithm. Moreover, electric field verification calculation has been carried out under AC and PR conditions. The results show that under uniform temperature condition, E-field strength is larger than that under iso-thermal condition. The overshoot coefficient of the bushing end and barrier reach 65% and 45%, respectively. The study can provide reference for the design of outlet structure of the converter transformer. © 2023 IEEE.

关键词： DC transformers

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Memory-Efficient Reversible Spiking Neural Networks

arXiv

引用

arXiv 2023年

作者： Zhang, Hong Zhang, Yu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Hangzhou China

Spiking neural networks (SNNs) are potential competitors to artificial neural networks (ANNs) due to their high energyefficiency on neuromorphic hardware. However, SNNs are unfolded over simulation time steps during the training process. Thus, SNNs require much more memory than ANNs, which impedes the training of deeper SNN models. In this paper, we propose the reversible spiking neural network to reduce the memory cost of intermediate activations and membrane potentials during training. Firstly, we extend the reversible architecture along temporal dimension and propose the reversible spiking block, which can reconstruct the computational graph and recompute all intermediate variables in forward pass with a reverse process. On this basis, we adopt the state-of-the-art SNN models to the reversible variants, namely reversible spiking ResNet (RevSResNet) and reversible spiking transformer (RevSFormer). Through experiments on static and neuromorphic datasets, we demonstrate that the memory cost per image of our reversible SNNs does not increase with the network depth. On CIFAR10 and CIFAR100 datasets, our RevSResNet37 and RevSFormer-4- 384 achieve comparable accuracies and consume 3.79× and 3.00× lower GPU memory per image than their counterparts with roughly identical model complexity and parameters. We believe that this work can unleash the memory constraints in SNN training and pave the way for training extremely large and deep SNNs. The code is available at https://***/mi804/***. Copyright © 2023, The Authors. All rights reserved.

关键词： Neural networks

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Risk Identification Method for Smuggled Frozen Meat in Urban Public Safety Awareness and Early Warning

Risk Identification Method for Smuggled Frozen Meat in Urban...

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2023 International Conference on Intelligent Communication and Networking, ICN 2023

作者： Li, Xueru Zhang, Yan Liu, Lingjie Tian, Ye Zhang, Yue Harbin Engineering University College of Computer Science and Technology Harbin China China Industrial Control Systems Cyber Emergency Response Team Beijing China Environment and Food and Drug Crime Investigation Detachment of Hangzhou Public Security Bureau Hangzhou China Xidian University Hangzhou Institute of Technology Hangzhou China Key Laboratory of Peace-Building Big Data of Zhejiang Province Zhejiang China

ISBN: (纸本)9798350357677

With the continuous growth in demand for meat and frozen products in the cold chain market, illegally smuggled frozen goods have quickly entered the market due to their low prices, leading to a series of food safety issues. This article proposes a method for identifying the risks of smuggled frozen meat for urban public safety awareness using the YOLOv7 model. The YOLOv7 model is used to detect data captured at various traffic checkpoints, obtaining spatiotemporal information of frozen goods vehicles. This information is then combined with map data to generate vehicle trajectory information. The trajectory similarity between the frozen vehicle trajectories and the specialized database of frozen transportation routes is analyzed using the EDwP distance algorithm. The EDwP algorithm employs a threshold-free approach, dynamically interpolating using the concept of projection, and automatically adapting to non-uniform sampling rates to address the issue of inconsistent trajectory data sampling rates. The experimental results of the YOLOv7-EDwP algorithm were verified by verifying the alerts generated in the recent period through on-site verification by a third-party inspection agency, with a recognition accuracy of 90.77%. This holds significant significance in the detection and warning of smuggled frozen meat. © 2023 IEEE.

关键词： Transportation routes

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Channel Modeling for RIS-Aided MIMO Communication System in Near- and Far-Fields 6

Channel Modeling for RIS-Aided MIMO Communication System in ...

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6th International Conference on Electronics technology, ICET 2023

作者： Yang, Qiping Chen, Ruifeng Zhang, Haoxiang Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China Institute of Computing Technology China Academy of Railway Sciences Corporation Ltd. Beijing China China Academy of Industrial Internet Ministry of Industry and Information Technology Beijing China

ISBN: (纸本)9798350337693

Recently, reconfigurable intelligent surface (RIS) and multiple-input multiple-output (MIMO) have drawn much attention as two potential technologies of 6G technology. RIS-aided MIMO communication system can provide desired channel performance. However, with the increase of RIS array and frequency, RIS is more likely to operate in near-field, where channel modeling based on plane wave model is no longer accurate. In this paper, near- and far-fields channel models of RIS-aided MIMO communication system are established using spherical wave and plane wave models, respectively. By deviating from the conventional modeling approach, we consider power radiation pattern and projection aperture in channel modeling, which well expresses the variations of signal phase and amplitude. Moreover, uniform planar wave model is used to characterize transmitter(Tx) and receiver(Rx) antennas, which is more suitable for practical scenarios. Based on the proposed model, received signal power of RIS-aided MIMO communication system is studied. From the simulation results, it is found that received signal power is largely affected by zenith and azimuth angles of Tx/Rx, frequency, amd distance between Tx/Rx and RIS array, and number of RIS array elements. In addition, since zenith and azimuth angles have different effects on projected aperture and power radiation pattern, received signal power is found to have different performance in near- and far-fields. © 2023 IEEE.

关键词： Wave propagation

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Detection-Triggered Recursive Impact Mitigation against Secondary False Data Injection Attacks in Microgrids

arXiv

引用

arXiv 2024年

作者： Liu, Mengxiang Zhang, Xin Zhang, Rui Zhou, Zhuoran Zhang, Zhenyong Deng, Ruilong The Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom The National Grid ESO Wokingham United Kingdom The State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou China

The cybersecurity of microgrid has received widespread attentions due to the frequently reported attack accidents against distributed energy resource (DER) manufactures. Numerous impact mitigation schemes have been proposed to reduce or eliminate the impacts of false data injection attacks (FDIAs). Nevertheless, the existing methods either requires at least one neighboring trustworthy agent or may bring in unacceptable cost burdens. This paper aims to propose a detection-triggered recursive impact mitigation scheme that can timely and precisely counter the secondary FDIAs (SFDIAs) against the communication links among DERs. Once triggering attack alarms, the power line current readings will be utilised to observe the voltage bias injections through the physical interconnections among DERs, based on which the current bias injections can be recursively reconstructed from the residuals generated by unknown input observers (UIOs). The attack impacts are eliminated by subtracting the reconstructed bias from the incoming compromised data. The proposed mitigation method can work even in the worst case where all communication links are under SFDIAs and only require extra current sensors. The bias reconstruction performance under initial errors and system noises is theoretically analysed and the reconstruction error is proved to be bounded regardless of the electrical parameters. To avoid deploying current sensors on all power lines, a cost-effective deployment strategy is presented to secure a spanning tree set of communication links that can guarantee the secondary control performance. Extensive validation studies are conducted in MATLAB/SIMULINK and hardware-in-the-loop (HIL) testbeds to validate the proposed method’s effectiveness against single/multiple and continuous/discontinuous SFDIAs. Copyright © 2024, The Authors. All rights reserved.

关键词： Cost effectiveness

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Study on Disturbance Propagation Characteristics of Power Grid and Evaluation of Temporal and Spatial Correlation Characteristics of Voltage Phase Trajectory 41

Study on Disturbance Propagation Characteristics of Power Gr...

引用

第41届中国控制会议

作者： Yibo Kong Changyou Feng Hongying Yang Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Xinjiang Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. National Electric Power Dispatching and Control Center of State Grid Corporation of China China Electric Power Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the access of large-scale new energy and power electronic equipment,as well as the influence of various random uncertain factors,the analysis and control of dynamic security of large power grids become particularly difficult,so it is of great practical significance to study the disturbance propagation characteristics of complex power *** is an important parameter that affects the security of power systems,and the voltage phase trajectory contains abundant power grid ***,based on the measured data,this paper quantitatively describes the characteristics of dynamic space-time distribution of the voltage,and numerically reveals the different influences of disturbance on different nodes and the characteristics of disturbance ***,the geometric characteristics of the measured voltage phase trajectory are mined,the new trajectory distance is defined,the characteristic trajectory plane is constructed,and the spatio-temporal evolution law of voltage phase trajectory is *** the sequel,through the density-based DBSCAN clustering method,the characteristic tracks of voltage movement are clustered and analyzed,and the temporal and spatial correlation characteristics of voltage movement trends of each node are measured,and the law of disturbance propagation is ***,based on the measured data of IEEE 39-bus system,the simulation analysis is carried out,and the effectiveness of the presented algorithm is verified.

关键词： Disturbance propagation Voltage phase trajectory Temporal and spatial correlation characteristics Trajectory clustering

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Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation

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Light(Science & Applications) 2023年第12期12卷 2826-2844页

作者： Weisong Zhao Xiaoshuai Huang Jianyu Yang Liying Qu Guohua Qiu Yue Zhao Xinwei Wang Deer Su Xumin Ding Heng Mao Yaming Jiu Ying Hu Jiubin Tan Shiqun Zhao Leiting Pan Liangyi Chen Haoyu Li Innovation Photonics and Imaging Center School of Instrumentation Science and EngineeringHarbin Institute of TechnologyHarbinChina Key Laboratory of Ultra-Precision Intelligent Instrumentation of Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbinChina Biomedical Engineering Department International Cancer InstitutePeking University Cancer Hospital and InstituteHealth Science CenterPeking UniversityBeijingChina The Key Laboratory of Weak-Light Nonlinear Photonics of Education Ministry School of Physics and TEDA Institute of Applied PhysicsFrontiers Science Center for Cell ResponsesNankai UniversityTianjinChina State Key Laboratory of Membrane Biology Beijing Key Laboratory of Cardiometabolic Molecular MedicineInstitute of Molecular MedicineNational Biomedical Imaging CenterSchool of Future TechnologyPeking UniversityBeijingChina Department of Control Science and Engineering Harbin Institute of TechnologyHarbinChina School of Mathematical Sciences Peking UniversityBeijingChina Unit of Cell Biology and Imaging Study of Pathogen Host Interaction The Center for MicrobesDevelopment and HealthKey Laboratory of Molecular Virology and ImmunologyShanghai Institute of Immunity and InfectionChinese Academy of SciencesShanghaiChina School of Life Science and Technology Harbin Institute of TechnologyHarbinChina PKU-IDG/McGovern Institute for Brain Research BeijingChina Beijing Academy of Artificial Intelligence BeijingChina Frontiers Science Center for Matter Behave in Space Environment Harbin Institute of TechnologyHarbinChina Key Laboratory of Micro-Systems and Micro-Structures Manufacturing of Ministry of Education Harbin Institute of TechnologyHarbinChina

In fluorescence microscopy,computational algorithms have been developed to suppress noise,enhance contrast,and even enable super-resolution(SR).However,the local quality of the images may vary on multiple scales,and these differences can lead to *** mapping methods fail to finely estimate the local quality,challenging to associate the SR scale ***,we develop a rolling Fourier ring correlation(rFRC)method to evaluate the reconstruction uncertainties down to SR *** visually pinpoint regions with low reliability,a filtered rFRC is combined with a modified resolution-scaled error map(RSM),offering a comprehensive and concise map for further *** demonstrate their performances on various SR imaging modalities,and the resulting quantitative maps enable better SR images integrated from different ***,we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.

关键词： resolution local enable

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