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16th Annual Conference of China Electrotechnical Society, CES 2021

作者： Huang, Lei Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9789811915277

In view of the issues such as frequency synchronization, load sharing and transient frequency regulation capability of gird forming renewable power converters in power system, a nonlinear virtual oscillator control (VOC) is presented. Based on Van der Pol oscillator, VOC controller which is composed of rotation, synchronization and magnitude regulation components is illustrated and its relationship with droop control is analyzed. VOC control strategy requires only local measurements and set-points of pre-specified power flow to realize communication-less decentralized control of grid-connected power converters and guarantees robust stability. To verify the feasibility, the proposed method is verified using a model comprising multiple VOC controlled converters. Results show that VOC converters are capable of dynamic synchronization, frequency stability and real-time droop characteristics regulation with different line impedance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electric load flow

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Research on Traction Optimization control Strategy for 10,000-Ton Heavy Haul Trains 19th

Research on Traction Optimization Control Strategy for 10,00...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Kunpeng Tang, Junjie Yang, Hui School of Electrical and Automation Engineering East China Jiaotong University Nanchang330013 China Jiangxi Provincial Key Laboratory of Advanced Control and Optimization Nanchang330013 China State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure Jiangxi Nanchang330013 China

ISBN: (纸本)9789819613823

Aiming at the problems of difficult control of electric traction equipment for heavy haul trains and low accuracy of control models, a distributed fuzzy sliding mode optimization control strategy for heavy haul trains based on a predictive compensation model is proposed. Firstly, based on the complex road condition information of heavy haul railways, a longitudinal dynamics model of heavy haul trains is established. Then, a long short-term memory neural network (LSTM) optimized by the Northern Goshawk Optimization (NGO) algorithm is used to predict and compensate the uncertain terms in the model. At the same time, a variable universe fuzzy algorithm (VUF) is used to improve the fast terminal sliding mode controller (FTSM). Finally, the improved controller is combined with the air braking strategy to jointly control the corrected model. The simulation results based on the heavy haul train operation simulation platform and real operation data show that the proposed method can effectively improve the handling stability and safety of 10,000-ton heavy haul trains. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Traction control

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Deployment of optoelectronic devices based on improved NSGA-II

Deployment of optoelectronic devices based on improved NSGA-...

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2023 International Conference on Mechatronic engineering and Artificial Intelligence, MEAI 2023

作者： Gong, Hua Sui, Guoshuang Xu, Ke Sun, Wenjuan Shi, Yiying College of Science Shenyang Ligong University Shenyang110159 China Liaoning Provincial Key Laboratory of Intelligent Optimization and Control of Ordnance Industry Liaoning Shenyang110159 China School of Automation and Electrical Engineering Shenyang Ligong University Liaoning Shenyang110159 China

ISBN: (纸本)9781510674608

In order to improve the security of the defended targets in our region and efficiently utilize various types of optoelectronic devices, the research is conducted on optoelectronic devices deployment within the region. With the objectives of maximizing the protection effectiveness and minimizing devices operational cost, a multi-objectives optimization model is established by considering constraints such as devices-target visibility conditions and device types, quantities, etc. Non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ) improved by Q-learning is designed to solve the model. To address the difficulty of fixed parameter settings adapting to dynamic changes, Q-learning is adopted to adaptively adjust the crossover probability and variation probability. In order to search for Pareto front solutions that are close to the global optimal more efficiently. The correctness of the model and the effectiveness of the algorithm are verified through simulation examples. © 2024 SPIE.

关键词： Optoelectronic devices

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Event-Triggered Energy Optimization of Wireless Sensor Networks 19

Event-Triggered Energy Optimization of Wireless Sensor Netwo...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Liu, Lu Song, Ruizhuo Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665472432

Aiming at limited communication and energy re-sources in wireless sensor networks (WSN s), this paper proposes an energy management scheme of WSNs via adaptive dynamic programming (ADP) based on event-triggered mecha-nism (ETM). The optimal control strategy obtained by iteration can schedule the sensor nodes and make the nodes switch between working and sleeping situations, thus improving the energy utilization and extending the service life of the energy-constrained WSNs. Firstly, the mathematical model of WSNs is established, and the state is estimated by extended Kalman filter (EKF) algorithm to improve the measurement accuracy. Then, ADP solves the designed value function to achieve the scheduling plan. On the premise of system stability, ETM is applied to activate the controller on demand, which can reduce communication burden and save WSNs energy consumption. Finally, the simulation experiment reveals that the proposed algorithm can reduce the unnecessary triggering times of the controller effectively while ensuring the requirements, and avoid data congestion and interaction resource waste. © 2022 IEEE.

关键词： Energy utilization

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

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Simulation and Analysis of PMSM with Segmented Halbach Magnet Array

Simulation and Analysis of PMSM with Segmented Halbach Magne...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Ge, Lijia Yan, Liang Xiang, Pengjie Zhou, Yuchen Aboelhassan, Ahmed School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China Electrical and Control Engineering Department College of Engineering and Technology Arab Academy for Science Technology and Maritime Transport Alexandria1029 Egypt Key Laboratory of More Electric Aircraft Technology of Zhejiang Province University of Nottingham Ningbo China Ningbo315100 China

ISBN: (纸本)9789811966125

This paper investigates the relationship between the output performance of PMSM and the number of the Halbach magnetic segments. The static magnetic simulation models of the Halbach with three to seven segments are established, and the spatial harmonic distribution of these magnetic arrays under the static magnetic field is analyzed. The simulation date indicates that the five-segment configuration has the best suppression effect on the 5th harmonic, and the seven-segment Halbach magnet array has the maximum fundamental amplitude of magnetic flux density. Then, the transient magnetic simulation models of these magnetic configuration are established by FEM, and the dynamic performance in PMSM is simulated and analyzed. By comparing the simulation data, it indicates that the electromagnetic output performance of five-segment magnetic configuration is the best. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Harmonic analysis

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Prediction of Element Component Content Based on Mechanism Analysis and Error Compensation 4

Prediction of Element Component Content Based on Mechanism A...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Lu, Rongxiu Deng, Biao Ding, Kanghao Yang, Hui Zhu, Jianyong Liu, Hongliang School of Electrical and Automation Engineering East China Jiaotong University Key Laboratory of Advanced Control and Optimization of Jiangxi Province Jiangxi Nanchang330013 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

To solve the difficulty of rapid and accurate detection of component content in the rare earth extraction process, a component content modeling method combining mechanism model and error compensation model based on just-in-time learning (JITL) was proposed. Considering the different dynamic characteristics of each section, the extraction section is simplified using the segmented-aggregation method, and the mechanism model of the rare earth extraction process based on material balance is established;in view of the error caused by the simplification of the model and the characteristics of some rare earth solutions with color features, the color features of rare earth solution samples are extracted by machine vision technology, and the error compensation model of the mechanism model is established by the just-in-time learning algorithm. Through the experimental verification of the field sample data of the praseodymium/neodymium (Pr/Nd) extraction process, the results show that the modeling method proposed in this paper is suitable for rapid and accurate detection of elemental component content in the rare earth extraction process with ionic color features. © 2022 IEEE.

关键词： Extraction

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Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 985-996页

作者： Lei Zou Zidong Wang Bo Shen Hongli Dong Guoping Lu College of Information Science and Technology Donghua UniversityShanghai 201620 Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesex UB83PHUK Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

关键词： Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation

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A Fault Detection Method and System for Highway Tunnel dome light Based on Improved YOLO with Locatization Loss Function 4

A Fault Detection Method and System for Highway Tunnel dome ...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Dai, Lizhen Tang, Cailing Yang, Gang Yang, Hui Luo, Jiang Chen, Zhaozhang East China Jiaotong University Key Laboratory of Advanced Control and Optimization of Jiangxi Province School of Electrical and Automation Engineering Jiangxi Nanchang330013 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Sufficient light intensity in the tunnel plays an extremely important role in ensuring the safety of driving in the tunnel. Tunnel dome light is the basic facility to ensure tunnel lighting. The traditional fault detection method is manual inspection, and the discovery of the problem is not timely. In this paper, a tunnel dome light fault detection method and system based on video monitoring is proposed. Constructing a tunnel dome light detection data set. The original positioning loss function in YOLOv5 is changed from CIOD_Loss function to SCALoss function, which is composed of side overlap (SO), corner distance (CD) and aspect ratio (AR) loss. So that the network can generate more penalties for low overlap positioning frames, and the network model has better positioning performance and faster convergence speed, it is more suitable for the dense and small target such as tunnel headlight. After improving the model, the recognition accuracy is improved by 13.1 %, and the positioning loss is also reduced. So that it can quickly and accurately locate the target to be detected. Finally, the fault lamp detection model is constructed to locate the specific location of the fault lamp. The experiment shows that the model has good performance, and it can effectively detect the state of tunnel dome light in real time and detect abnormal working conditions. © 2022 IEEE.

关键词： Location

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Reducing the energy consumption required for the disassembly process implemented on an assembly and disassembly line 24

Reducing the energy consumption required for the disassembly...

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24th International Conference on control Systems and Computer Science, CSCS 2023

作者： Marius-Adrian, Paun Elena, Dragomir Otilia Florin, Dragomir Stelian, Iliescu Sergiu Eugenia, Minca Octavian Gabriel, Duca Valentin, Gurgu Ion University 'Politehnica' of Bucharest Department of Automation and Industrial Informatics Bucharest Romania Valahia University of Targoviste Faculty of Electrical Engineering Electronics and Information Technology Targoviste Romania University 'Politehnica ' of Bucharest Faculty of Automatic Control and Computers Bucharest Romania University 'Dunarea de Jos ' of Galati Department of Automation and Electrical Engineering Galati Romania Institute of Multidisciplinary Research for Science and Technology Valahia University of Targoviste Targoviste Romania

ISBN: (纸本)9798350313390

This paper proposes a method to reduce the energy consumption of an industrial disassembly process implemented on a production line by using an energy-efficient secondary disassembly process. In the case of defective products, the flow directs the simple product with priority to be disassembled in workstation (WS) 7. Therefore, all defective products are redirected to WS7. The disassembly of all simple products in WS7 is problematic for two reasons: the power consumption of WS7 is high compared to the other workstations, additionally there is an increased possibility of bottlenecks in the production line due to the high disassembly time. The proposed solution to reduce the possibility of deadlock and reduce power consumption is to redirect the defective products to the flexible cell (FC). Handling robots located in neighboring stations will participate collaboratively in the disassembly process. The control structure ensures that the two robots 'meet' in the boundary plane of WS3 with WS4 and disassemble each component through collaborative tasks. Collaborative control of disassembly is thought of as a solution to the global 'fluidization' of production, removing the bottleneck, from the overall flow, but also as an ingenious solution to reduce energy consumption. © 2023 IEEE.

关键词： Assembly

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