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arXiv 2023年

作者： Gehring, Nicole Irscheid, Abdurrahman Deutscher, Joachim Woittennek, Frank Rudolph, Joachim Institute of Automatic Control and Control Systems Technology Johannes Kepler University Linz Austria Systems Theory and Control Engineering Saarland University Germany Institute of Measurement Control and Microtechnology Ulm University Germany Institute of Automation and Control Engineering UMIT TIROL Private University for Health Sciences and Health Technology Austria

This paper gives an overview of the control of distributed-parameter systems using normal forms. Considering linear controllable PDE-ODE systems of hyperbolic type, two methods derive tracking controllers by mapping the system into a form that is advantageous for the control design, analogous to the finite-dimensional case. A flatness-based controller makes use of the hyperbolic controller canonical form that follows from a parametrization of the system’s solutions. A backstepping design exploits the strict-feedback form of the system to recursively stabilize and transform the subsystems. © 2023, CC BY-NC-SA.

关键词： State feedback

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Covid-19 Epidemic Trend Prediction Based on CNN-StackBiLSTM 11

Covid-19 Epidemic Trend Prediction Based on CNN-StackBiLSTM

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Li, Zhenyu Wang, Yang Wang, Yanwei Zheng, Ying Su, Housheng School of Artificial Intelligence and Automation Huazhong University of Science and Technology China-Belt and Road Joint Laboratory On Measurement and Control Technology Wuhan430074 China School of Mechanical & Electrical Engineering Wuhan Institute of Technology Hubei Wuhan430073 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In late 2019, the novel coronavirus (COVID-19) became a major health hazard around the world. Recently, the COVID-19 has spread widely in most countries and regions and the number of infected people continues to grow rapidly. Therefore, it is essential to research the development trend of the epidemic. The prediction of the number of infections and deaths is critical and helpful for developing health and epidemic prevention strategies and even curbing the epidemic. In this paper, a one-dimensional convolutional neural network combined with the stacked long-short-term-memory network model (CNN-StackBiLSTM) is proposed for the time-series prediction of cumulative cases and daily new cases. The local feature is extracted by CNN. The stacked BiLSTM captures the deeper characteristics of the time-series data. By combining the two networks, the proposed method simultaneously considers the information of temporal and spatial domains and can achieve accurate prediction results. Examples in Taiwan and Italy demonstrate the effectiveness of the proposed method. The proposed method is compared with LSTM, BiLSTM, and GRU. The mean absolute error, mean square error, R2 score, and root mean square error are calculated to quantificationally measure the different models. The results indicate the proposed method performs well in the prediction of both new daily confirmed cases and cumulative confirmed cases. © 2022 IEEE.

关键词： COVID-19

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Equivalent Ratio of Frequency Regulation Resources Based on Derivation of Open-Loop control Frequency Deviation

Equivalent Ratio of Frequency Regulation Resources Based on ...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Jia Ning Hanxiang Wang Ying Wang School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University Nanjing China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

The conventional approach to frequency regulation predominantly relies on thermal and hydroelectric power generation units. As a growing variety of frequency regulation resources become accessible to power systems, there is significant variation in their performance characteristics, it is important to quantify their capabilities in the frequency service markets. This study introduces a technique to calculate the equivalent ratio of these resources by analyzing their primary response to frequency deviations derived from open-loop control. Based on the rotor motion equation of the generator, this paper constructs a load frequency control model incorporating two distinct regulation resources, linearize their outputs, and integrate them into the model. Through differential equations, this paper derives analytical expressions for the frequency deviation curve, enabling the determination of key frequency metrics. The equivalent ratio is then calculated by comparing the output power of resources with similar performance indicators. Finally, the paper investigates the impact of diverse parameters on the computation of the equivalent ratio employing simulation-based experimental analysis.

关键词： measurement Computational modeling Rotors Hydroelectric power generation Mathematical models Generators Regulation Power systems Frequency control Load modeling

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Research on Automatic Design Method of Double Freeform Surface Ar-Hud Imaging System

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SSRN 2024年

作者： Guo, Xiangxin Mu, Da School of Physics and Optoelectronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China Photoelectric Measurement and Control Technology Institute Changchun University of Science and Technology Jilin Changchun130022 China

An automotive augmented reality head-up display (AR-HUD) system is affected by many complex phenomena, such as the influence of moving eyeballs, drivers’ heights, additional aberration correction required due to windshields, and variable structural constraints of vehicle model and other factors. Consequently, it is difficult to optimize the design of such a system. To mitigate this problem, we propose an automatic design method for the automotive AR-HUD imaging system, which is suitable for two freeform surfaces and any type of windshield structure. Based on Malus Law, all the characteristic data points of the freeform surface in the full field of view and full aperture are calculated. Subsequently, the points are fitted to the free-form surface represented by polynomials. The initial structure of the free-form off-axis system with a good imaging quality is directly obtained. Finally, the optical path feedback iterative method is used to further optimize the data point cloud of each field of view to determine the best fitting coefficients, generate the required freeform mirror, and obtain the final structure of the AR-HUD optical system. The proposed AR-HUD designs for an eye-box of and a field of view of exhibit excellent optical performance, demonstrating the feasibility and superiority of the proposed design framework. © 2024, The Authors. All rights reserved.

关键词： Augmented reality

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Automatic Design of Multi-Light Field Ar-Hud Based on Fresnel Ladder Freeform Mirror

SSRN

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SSRN 2024年

Conventional augmented reality head-up display (AR-HUD) suffers from various issues, such as large volume, single-image layer single-focal surface display, difficult optimization design of special face shape, and low definition under wide frame. To overcome these limitations, we propose an AR-HUD imaging system design method with Fresnel stepped free-form mirror, which can be adapted to any type of given windshield. First, the Malus' law is used to solve the discrete point cloud in the initial architecture. Second, the stepped Fresnel region is constructed by the field of view (FOV) extension method to directly obtain a good initial structure. Last, the optical path feedback iterative method is used to further optimize the data point cloud in each FOV and determine the best fitting coefficients. Using this method, two kinds of Fresnel AR-HUD structure layout, i.e., horizontal and vertical, are designed. Simulation results show that the proposed design framework can effectively reduce the volume by 20%, realize multi-layer distribution of image information display at different distances, integrate effectively with the AR, and improve image quality synchronization, which prove its feasibility and superiority. © 2024, The Authors. All rights reserved.

关键词： Ladders

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Indication Detection of Electric Energy Meter Based on YOLOv5

Indication Detection of Electric Energy Meter Based on YOLOv...

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作者： Bao-hua, Yang Kang-ming, Huang Yu, Sun Hong-jun, Guo School of Information Ensgineering Changzhou Vocational Institute of Mechatronic Technology Changzhou213164 China Department of Computer Engineering Asian University Suwon443-749 Korea Republic of Jiangsu Xinhuayu Measurement and Control Technology Co. Ltd Changzhou213164 China Jiangsu Xiangguo Automation Technology Co. Ltd Changzhou213164 China

With the continuous popularization of instruments, the inspection and testing of instruments have received more and more attention. This method is mainly divided into two links: target detection and information recognition. First, the instrument is located by OpenCV findcircuits function, and the instrument area is extracted. Then, the relevant methods of digital image processing are used for preprocessing, extracting the number information of the instrument panel, and establishing the data set. By using OpenCV to realize image edge detection, image segmentation and target area recognition, and then the deep learning methods are used are YOLOv3, YOLOv4 and YOLOv5 algorithms to realize the recognition of indications, the results show that the recall, precision, AP and F1 indicators of YOLOv5 were 95.26% and 95.89%, respectively, 96.29% and 95.77%, the above results of YOLOv5 are significantly improved compared with YOLOv3 and YOLOv4. The use of bottleneckcsp1 and bottleneckcsp2 in the neck can improve the network speed while ensuring accuracy, which shows that YOLOv5 is a very suitable real-time test method for instrument readings. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Autonomous Localization Method for Railway Trains Based on Multi-Source Information Fusion

Autonomous Localization Method for Railway Trains Based on M...

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Electronic engineering and Information Systems (EEISS), International Conference on

作者： Hanxuan Zhang Ju Huo Muyao Xue Jianbao Zhou School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Shanghai Space Propulsion Technology Research Institute Shanghai China Harbin Nuoxin University of Technology Measurement and Control Technology Co. Ltd. Harbin China

ISBN: (数字)9798350351033

ISBN: (纸本)9798350351040

Aiming at the problems of high cost and difficult maintenance in the practical application of the traditional "vehicle-ground cooperation" train positioning technology in special section railway projects. In this paper, a method for autonomous positioning of railway trains based on multisource information fusion is proposed. First, develop a kilometer mark detection thread based on VINS Fusion, and build a lightweight optical symbol recognition system to identify the character area of the kilometer mark to obtain the position information of the electronic map. Secondly, based on the LSD line detection algorithm combined with the way of dynamically expanding the line, the coordinates of the vertex coordinates of the kilometer mark are extracted. Then, a global optimization objective function containing the position information constraints of the kilometer mark is established, and the global positioning accuracy is improved through the graph optimization method. This solves the problem that existing intelligent positioning of railway trains cannot eliminate accumulated errors in the absence of loop closure detection. Finally, the semi-physical simulation results show that the positioning error of the original positioning system can be reduced by more than 57%.

关键词： Location awareness Costs Simulation Symbols Optimization methods Linear programming Rail transportation

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Data Security Risk Assessment Method of Intelligent and Connected Vehicles Based on Data Security Classification and Grading 8

Data Security Risk Assessment Method of Intelligent and Conn...

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8th IEEE International Conference on Intelligent Transportation engineering, ICITE 2023

作者： Wang, Liyong Jin, Long Ji, Haojie Wang, Jingyan Chen, Yupeng Fang, Junzhe State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Ministry of Education Beijing Information Science & Technology University Key Laboratory of Modern Measurement & Control Technology Beijing China State Key Laboratory of Intelligent Vehicle Safety Chongqing China China Automotive Engineering Research Institute Co. Ltd Chongqing China

ISBN: (纸本)9798350314212

The rapid development of intelligent and connected vehicle (ICV) has brought increasing communication data and valuable data assets. However, the diversity and complexity of ICV data make it hard to carry out data security risk assessment. Aiming at the problem, this paper proposes an effective analytical method for the data security risk assessment method of ICVs. Considering the typical scenario for the generated data of ICVs, a data security classification and grading framework is constructed from the aspects of in-vehicle data, personal data, and external environment data. The data security risk assessment model is built for ICVs and includes functional modules such as asset identification, threat identification, impact assessment, vulnerability identification, and risk assessment. This work provides methods and security management and control strategy support for ICV data security risk assessment. © 2023 IEEE.

关键词： data classification and grading data security Intelligent and connected vehicles risk assessment

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Adaptive control Strategy of Wind-Solar-Storage Parallel Virtual Synchronous Generator Parameters Based on Variable Universe Fuzzy control

Adaptive Control Strategy of Wind-Solar-Storage Parallel Vir...

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Power and Electrical technology Conference (APET), Asia

作者： Zhao Zijun Wang Hui Zhang Zhuanqin Yang Zhilong Zhang Yadong National Local Joint Engineering Research Center for Smart Distribution grid Measurement and control with Safety Operation Technology Changchun Institute of Technology Changchun China

Virtual Synchronous Generator technology improves the frequency dynamic performance of the system by introducing virtual inertia and damping coefficients into the power electronic inverter. In order to further suppress power oscillations and solve the problem that constant virtual parameters cannot take into account the maximum frequency overshoot and response speed, firstly, a small-signal model of active and reactive power rings of virtual synchronous machine is established to study the influence of virtual inertia on the frequency stability and power equalization effect of parallel connection of multiple machines. Secondly, based on the fuzzy control method in variable universe, the control strategy of coordinated adaptive adjustment of the virtual inertia of the parallel system according to the output angular frequency is proposed, and at the same time, the automatic adjustment of the virtual damping coefficient with the inertia is realized by combining with the appropriate damping ratio. Finally, the parallel parameter matching principle is designed so that the output power can be distributed according to the capacity ratio. Two different virtual synchronous machine control strategies are compared and analyzed by matlab/simulink to verify the correctness and feasibility of the proposed adaptive control strategy.

关键词：

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Research on Resonance Suppression Method of Multi-Inverter Parallel System Based on Improved Fcs-Mpc

SSRN

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SSRN 2024年

作者： Chunhui, Liang Li, Jinfa Zuo, Xiaoyang Huang, Chenglong Liu, Renjie School of Electrical and Information Engineering Changchun Institute of Technology Changchun130025 China National local joint Engineering Research Center for Measurement and Control and Safe Operation Technology of Intelligent Distribution Network Changchun130103 China

A mathematical model of the multi-NPC three-level LCL inverter system is constructed with the goals of suppressing the resonance of the multi-inverter grid-connected system, improving the output power quality, and improving the pure output current waveform on the grid side of the system. Firstly, The system's resonance characteristics are studied by the equivalent NORTON model of multiple inverters in parallel. Secondly, because of the resonance existing in the multi-inverter parallel system, by integrating active damping and improving the Finite control Set Model Predictive control (FCS-MPC) method, realize the harmonic design in both the low- and high-frequency domains. It can successfully reduce the resonance phenomenon and raise the system's general stability. Meanwhile, It is possible to greatly lower the harmonic distortion rate and enhance the output current waveform. Finally, two parallel NPC three-point flat LCL filters inverters were built for simulation analysis, and the suggested analysis method's viability and accuracy were confirmed. © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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