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2nd IEEE China International Youth Conference on Electrical Engineering, CIYCEE 2021

作者： Jing, Zhengting Fu, Yongsheng Chen, Jianfei Ren, Haipeng Xi'An Technological University School of Electrical Information Engineering Xi'an710021 China Xi'An Technological University School of Mechatronic Engineering And the School of Electrical Information Engineering Xi'an710021 China University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States Xi'An Technological University School of Mechatronic Engineering Xi'an710021 China Shaanxi Key Laboratory of Comple System Control and Intelligent Information Xi an University of Technology Xi'an710048 China

ISBN: (纸本)9781665400640

Three-phase four-leg four-wire voltage source inverter (3P4L4W VSI) attracts more attention in many power electronics applications due to its flexibility for both balanced and unbalanced loads, where the power efficiency is a critical point. Conventional Si semiconductor devices suffer from large switching loss due to large parasitic capacitances and thus limit its switching frequency. As a result, it further limits the power density and efficiency improvement. The SiC/Si hybrid switch formed by SiC-MOSFET and Si-IGBT in parallel (SiC/Si HyS) can improve the switching frequency with high efficiency and low cost, which helps to design a power converter with high power density and high efficiency. However, the application of SiC/Si HyS in 3P4L4W faces some challenges, such as the drive circuit design, the proper delay selection, etc.. In this paper, a SiC/Si HyS based 3P4L4W VSI is introduced and the optimal turn-off time delay selection for the SiC/Si HyS used in 3P4L4W VSI is analyzed. A systematical way to calculate the power loss in the SiC/Si HyS is presented. A 5-kW/50kHz 3P4L4W VSI is taken as an example for validating the theory and method. It is found the peak efficiency of the 3P4L4W VSI is 97.5%, and the unbalanced phase load leads to more power loss and degrade the efficiency. The work in this paper provides practical guidance for a SiC/Si HyS based 3P4L4W VSI inverter design. © 2021 IEEE.

关键词： Silicon carbide

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A Summary of Research on Combustion Stability of Coal-fired Power Station Boilers

A Summary of Research on Combustion Stability of Coal-fired ...

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Chinese Automation Congress (CAC)

作者： Guoyuan Cai Yuguang Niu Xuefei Liu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing P. R. China School of Control and Computer Engineering North China Electric Power University Beijing P. R. China

ISBN: (数字)9781665426473

ISBN: (纸本)9781665426480

The research on the combustion stability of coal-fired power plant boilers is related to the safe operation and economic benefits of the boiler. The combustion stability judgement plays an important role for the assessment of flexibility retrofit with coal-fired power plants participating in deep peak-regulating operation. Therefore, the study of combustion stability judgment has always been a hot research direction. This paper briefly introduces the development history of boiler flame combustion stability research, and focuses on two popular research directions in this field in recent years, namely flame image combustion stability detection method and multi-information fusion combustion Stability testing methods, briefly summarize the development trends of these two research directions and their respective advantages. Then, the current research status and problems in this field are put forward three aspects of thinking and suggestions. Finally, several problems that need to be solved in the future development of combustion stability research are summarized.

关键词： Economics Automation Furnaces Fires Boilers Market research Combustion

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Variable Selection Method Based on Partial Mutual Information and Its Application to NOx Emission Prediction 39

Variable Selection Method Based on Partial Mutual Informatio...

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39th Chinese control Conference, CCC 2020

作者： Tianmu, Q.I.N. Jinzhe, Zhang Mo, Y.O.U. Tingting, Yang North China Electric Power Research Institute Co. Ltd. Beijing100045 China North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering Beijing102206 China

ISBN: (纸本)9789881563903

Data-driven modeling methods are widely used in industrial processes as the foundation of control and optimization. The selection of optimal variable set plays an important role in model performance. In order to enhance the model prediction accuracy, a partial mutual information (PMI) method was proposed to select the optimal variable set. Benchmarks were used to validate the effectiveness of PMI method. Then, PMI method was applied to select main influencing factors of NOx emission of coal-fired boiler and the selection results were used as inputs of three different data-driven models. The comparison between the models with or without variable selection was made. The results showed that the PMI method enhanced the model prediction accuracy and avoided the over-fitting problem. © 2020 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Coal fired boilers

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SVD based scale transform invariant observable degree for LTI system

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Science China(Information Sciences) 2021年第3期64卷 246-248页

作者： Quanbo GE Peng ZHUO Hongli HE Zhentao HU Zhansheng DUAN Junzhi YU Shenzhen Institute of Guangdong Ocean University School of Automation Hangzhou Dianzi University Test Institute Chinese Flight Test Establishment College of Computer and Information Engineering Henan University The Center for Information Engineering Science Research Xi'an Jiaotong University State Key Laboratory of Complex System Management and Control Institute of AutomationChinese Academy of Sciences

Dear editor,The basic concept of observability is used to express the possibility to recover the state from measurements in modern control theory [1–3]. It is a qualitative parameter,which cannot reflect the observable degree(OD) ability [4,5].Therefore, the OD is presented to quantitatively obtain the function. The quantitative parameter is effective for indicating the exact degree of estimation ability.

关键词： observability matrix observable degree singular value decomposition scale transform invariance linear system linear relation

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Learning-Based Energy-Efficient Channel Selection for Edge Computing-Empowered Cognitive Machine-to-Machine Communications 91

Learning-Based Energy-Efficient Channel Selection for Edge C...

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91st IEEE Vehicular Technology Conference, VTC Spring 2020

作者： Liao, Haijun Zhou, Zhenyu Ai, Bo Guizani, Mohsen North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electric and Electronic Engineering Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China University of Idaho Electrical and Computer Engineering Department Moscow United States

ISBN: (数字)9781728152073

ISBN: (纸本)9781728152073

In this paper, we study the channel selection problem in edge computing-empowered cognitive machine-to-machine (CM2M) communications, where a massive number of machine type devices (MTDs) offload their computational tasks to a nearby edge server by opportunistically using the spectra that are temporarily unoccupied by primary users (PUs). We formulate the channel selection problem as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to develop a learning-based energy-efficient solution named SEB-EXP3. It can find the long-term optimal channel selection strategy with guaranteed performance based on local information, while simultaneously achieving service reliability awareness, energy awareness, and data backlog awareness. Four heuristic algorithms are compared with SEB-EXP3 to demonstrate its effectiveness and reliability under various simulation settings. © 2020 IEEE.

关键词： Edge computing

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Redundancy reduction penalty term of loss function in deep neural network

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Knowledge-Based systems 2025年

作者： Xueheng Hu Shuhuan Wen H.K. Lam Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Yanshan University Qinhuangdao 066004 Hebei Province China The Department of Engineering King’s College London London WC2R 2LS United Kingdom

In this paper, we propose a novel regularization algorithm that is introduced as a penalty term to the loss function. Differing from conventional L1 and L2 regularization methods, our approach does not aim to diminish the weights of individual neurons or enforce sparsity by driving certain neurons to zero. Instead, it functions by increasing the differences between neurons and enhancing the diversity of neurons within each layer. Our method incorporates ensemble learning techniques by treating the layer weight matrix as a collective learning model, where each neuron serving as a weak learner within the layer. The proposed algorithm improves the performance of DCNN by simultaneously considering the distance between multiple filters in the same layer. This algorithm reduces the redundancy of the parameter layer filters in DCNN and enhances its robustness. The penalty term proposed by our algorithm dynamically adjusts its value in a cyclical manner, compelling the neural network to navigate away from its current gradient state. In the parameter space, different weights correspond to different locations. The proposed algorithm quantifies the distance between neurons and iteratively increases the distance between neurons during thereby encouraging greater diversity within the network. Experimental evaluations demonstrate the effectiveness of our algorithm in enhancing neural network performance without requiring adjustments to other hyper-parameters.

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Sparse Large-Scale Fading Decoding in Cell-Free Massive MIMO systems

arXiv

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arXiv 2022年

作者： Chen, Shuaifei Zhang, Jiayi Björnson, Emil Demir, Özlem Tugfe Ai, Bo School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China Department of Computer Science KTH Royal Institute of Technology KistaSE-16440 Sweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Cell-free massive multiple-input multiple-output (CF mMIMO) systems are characterized by having many more access points (APs) than user equipments (UEs). A key challenge is to determine which APs should serve which UEs. Previous work has tackled this combinatorial problem heuristically. This paper proposes a sparse large-scale fading decoding (LSFD) design for CF mMIMO to jointly optimize the association and LSFD. We formulate a group sparsity problem and then solve it using a proximal algorithm with block-coordinate descent. Numerical results show that sparse LSFD achieves almost the same spectral efficiency as optimal LSFD, thus achieving a higher energy efficiency since the processing and signaling are reduced. Copyright © 2022, The Authors. All rights reserved.

关键词： Decoding

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Highly Sensitive and Rapidly Responding Room-Temperature NH3 Gas Sensor that is Based on Exfoliated Black Phosphorus

SSRN

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SSRN 2022年

作者： Han, Dan Han, Xiaomei Zhang, Xiaqin Wang, Weili Li, Donghui Li, Hongwei Sang, Shengbo Shanxi Province Cancer Hospital Chinese Academy of Medical Sciences Cancer Hospital Shanxi Medical University Taiyuan030000 China Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System The Ministry of Education Taiyuan University of Technology Taiyuan030024 China

Black phosphorus (BP) has recently attracted significant interest in gas sensing because of its outstanding electronic and optical properties. In this paper, we demonstrated a series of gas sensors for detecting NH3 at room temperature that were based on BP nanosheets that were exfoliated for various durations. The BP nanosheet gas sensors showed excellent sensitivity for the detection of NH3 down to 100 ppb (~32%) under ambient conditions compared to previous reports. The BP nanosheets that were exfoliated for 60 min showed the highest response to 100 ppm NH3, namely, 121%, which was 2.5 times greater than the response of ground BP. The corresponding sensor also exhibited a stable response in the humidity range of 22% RH to 35% RH, which is the typical humidity range for non-rainy days. Moreover, the prepared NH3 gas sensor showed high selectivity, fast response and recovery, and excellent repeatability. According to various experimental and theoretical studies, the response and binding energy of BP towards NOx were higher than those towards NH3. However, very interestingly, the response of the exfoliated BP nanosheets to NH3 was higher than that to NOx in our work. The selectivity transformation from NOx to NH3 was mainly caused by the different layer spacing of the ground BP and the change in spacing between the BP nanosheet layers with different exfoliation times, increased oxygen incorporation, phosphate ions and defects that is induced by the liquid-phase exfoliation process, which led to the variations in its band gap and surface states. © 2022, The Authors. All rights reserved.

关键词： Nanosheets

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3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

arXiv

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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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Real-time and ultrafast optical pulse quantization based on slicing the supercontinuum

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Chinese Optics Letters 2021年第8期19卷 69-74页

作者： Ya Guo Qiang Cai Zhiwei Jia Bingjie Xu Zhensen Gao Qianwu Zhang Ruonan Zhang Adonis Bogris K.Alan Shore Yuncai Wang Pu Li Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUnited Kingdom

All-optical analog-to-digital conversion is a paramount issue in modern science. How to implement real-time and ultrafast quantization to optical pulses with different intensities in an all-optical domain is a central problem. Here, we report a realtime demonstration of an all-optical quantization scheme based on slicing the supercontinuum in a nonlinear fiber. In comparison with previous schemes through off-line analysis of the power of different optical spectral components in the supercontinuum, this, to the best of our knowledge, is the first demonstration of such functionality online in the time ***, the extinction ratio among the quantized outputs can exceed 10 d B, which further confirms the feasibility of the proposed quantization scheme. The current 3 bit resolution in the proof-of-principle experiment is limited by the current experimental condition, but it can be expected to be greatly enhanced through improving both the spectral width of the generated supercontinuum and the number of filtering channels used.

关键词： all-optical analog-to-digital conversion photonic quantization all-optical signal processing supercontinuum generation

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