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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： He, Ruoyu Li, Yihang Jia, Min Zhang, Peng Liu, Bin Tianjin University of Technology Tianjin School of Electrical Engineering and Automation China

ISBN: (纸本)9798350366600

A path planning method based on point cloud for robotic arm movement was proposed, which provides the 3D point and its vector direction for each moving position. First, an effective filtering algorithm is utilized to smooth the original point cloud. Then, the least squares method is employed to perform plane fitting on local regions of the filtered point cloud. Finally, the points with the corresponding normal vectors could be obtained for guiding the robotic arm movement. Experiments were designed to evaluate our method. Two filtering algorithms are carefully compared and chosen to simultaneously guarantee the accuracy of the gathered points and normal vectors, an evaluation metric is proposed. The point cloud of a standard sphere was acquired and fitted to calculate the sphere center. Each point and its normal vector determine one spatial line. The distance from the sphere center to each spatial line is defined as the quantitative indicator of the evaluation metric. Experimental results proved that the proposed method and evaluation metric are feasible and effective for precise motion control of robotic arms. © 2024 IEEE.

关键词： Wiener filtering

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Droop-Free Distributed Control Strategy for DC Microgrids with Single Variable Transmission 7

Droop-Free Distributed Control Strategy for DC Microgrids wi...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Liu, Hanying Liu, Xiaofang Zhang, Zehua Wang, Panbao School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350359558

In this paper, a distributed control strategy based on consensus algorithm for DC microgrids is proposed to realize the goal of average bus voltage restoration and current sharing by exchanging only single variable between each converter. Conventional control often requires the transmission of multiple messages to accomplish the control goal, however, more data transmitted results in higher communication requirements and the greater computational burden. Therefore, in the scheme proposed in this paper, the voltage and current are effectively combined into single integrated variable for transmission, and the droop control in the primary control is removed while the secondary controller is enabled to enhance the dynamic performance. The performance of the proposed scheme is verified by the PLECS platform under the working conditions of load switching and plug-and-play to verify its superiority. © 2024 IEEE.

关键词： Controllers

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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multiphysical analysis and motor design optimization. This article proposes a new method for thermal steady state modeling and analysis based on transfer learning (TL), which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on TL is developed: the model is pretrained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then, the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R^{2} and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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A Queue-length Threshold-based Control Strategy and Queueing-Analytic Model for CAVs at Signal-Free Intersections 4

A Queue-length Threshold-based Control Strategy and Queueing...

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4th International Conference on Control Theory and Applications, ICoCTA 2024

作者： Zhang, Jiaqi Yang, Qiaoli Lanzhou Jiaotong University School of Automation and Electrical Engineering Lanzhou China

ISBN: (纸本)9798331506155

The primary challenge in managing signal-free intersections in a connected environment is the allocation of right of way for connected and autonomous vehicles (CAVs) in conflicting directions. The stochastic and unpredictable arrivals of CAVs generally result in uncertainties regarding their queueing process and delays at signal-free intersections, which must be considered in the management of traffic flow. In this paper, we propose a queue-length threshold-based control strategy for the management of CAVs at signal-free intersections, thereby improving traffic effectiveness and reducing delays. This strategy is designed to dynamically adjust the right-of-way based on the fluctuations in CAV queue length at intersections. To explicitly evaluate the performance of the proposed control strategy, we further develop a queueing model and derive some basic traffic performance metrics. In addition, a series of numerical experiments was conducted to illustrate and analyze the effectiveness of the proposed strategy under various traffic conditions. Our results indicate that queueing performance at signal-free intersections can be affected by road storage capacity, traffic volume, and strategy settings. © 2024 IEEE.

关键词： Stochastic systems

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Research on the Identification Method of ZPW-2000 Frequency Shifted Signal based on Auxiliary Classifier Generative Adversarial Network 5

Research on the Identification Method of ZPW-2000 Frequency ...

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5th International Conference on Big Data and Artificial Intelligence and Software engineering, ICBASE 2024

作者： Liu, Wenjuan Wu, Xiaochun Lanzhou Jiaotong University School of Automation and Electrical Engineering Lanzhou China

ISBN: (纸本)9798331506612

As the track frequency shifted signals will cause signal mistranslation when subjected to interference. Therefore, it is very important to achieve the correct recognition of lowfrequency information in the case of noise, but the signal mistranslation caused by noise interference in the field is episodic, and a large number of datasets cannot be used for model training. In this paper, we propose to use Auxiliary Classifier Generative Adversarial Network (ACGAN) to achieve the data expansion of the signal, which provides the data basis for the classification and recognition of the signal. The results show that the method in this paper can effectively assist the training of the signal classification and recognition model, and can improve the classification and recognition accuracy from 90.55% to 97.46%. © 2024 IEEE.

关键词： Generative adversarial networks

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Passivity-Based Design of Capacitor Current Feedback Active Damping for Inverter-Side Current Controlled LCL-Type GCIs 49

Passivity-Based Design of Capacitor Current Feedback Active ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Huang, Yu Xie, Chuan Zou, Jianxiao School of Automation Engineering Uestc Chengdu China

ISBN: (纸本)9798350331820

For LCL type grid-connected inverters, inverter-side current control (ICC) mode is more promising for industrial applications for the convenience in the protection of power switches, e.g., IGBTs. However, the time delay in digital control causes the limited stable region of single-loop ICC. To enhance the stability of the system, capacitor-current-feedback active damping (CCF-AD) has been widely used to achieve the dual-loop current control. However, most of the existing designs of CCF-AD are under grid-side current control, while the passivity-based design of CCF-AD for the ICC has yet to receive much attention. For achieving passive output admittance of the inverter, this paper reveals a small delay needs to be introduced into the CCF-AD loop for the ICC. The parameter design of CCF-AD is detailed in this paper. Finally, the experimental results verify the theoretical analysis. © 2023 IEEE.

关键词： Electric current control

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Dynamic Path Planning Algorithm for Dual-robot Systems Based on Minimum Manipulability Constraints

Dynamic Path Planning Algorithm for Dual-robot Systems Based...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Li, Wei Cong, Yongzheng Shen, Zixiang Du, Haibo Zhu, Wenwu School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (纸本)9798350384185

In response to the safety and reliability concerns in dynamic path planning for dual-robot systems, this paper proposes a spatio-temporal A* path planning algorithm based on minimum manipulability ***, the algorithm extends the child nodes of the spatio-temporal A* algorithm using spatial velocity vectors, altering the search space, and increasing the turning cost to achieve smoother path ***, this paper proposes incorporating minimum manipulability constraints into the evaluation function of the spatio-temporal A* algorithm to enhance the flexibility of robots and the safety and reliability of ***, it increases the weight coefficient of the heuristic function to improve the efficiency of the *** results demonstrate that the proposed algorithm can plan smooth, safe, and reliable paths. © 2024 IEEE.

关键词： Robot programming

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Multi-Agent Air Combat Decision-making Based on Battlefield Attention Information 21

Multi-Agent Air Combat Decision-making Based on Battlefield ...

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21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Wang, Yihuan Mal, Yaofei Wang, Jiangyun Yuan, Haitao Wang, Meijia Mal, Hanbo Beihang University School of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350365221

With the rapid development of artificial intelligence and neural networks, deep reinforcement learning has achieved remarkable results in a series of complex sequential decision-making problems. The application of multi-agent reinforcement learning in air combat game scenarios is also booming. In the use of reinforcement learning for multi-agent air combat decision-making, the scalability and transferability of the model have become critical issues. Designing a multi-agent air combat decision-making framework with solid scalability, robustness, and rapid convergence has become a research hotspot in various countries. To address this problem, this paper proposes a multi-agent air combat decision-making framework based on attention mechanism transfer and designs a 2D air combat simulation environment for this framework. The decision-making process of this framework is divided into two stages. First, course learning is carried out in the designed essential air combat environment to enhance the aircraft's combat capability. Then, the trained strategy is transferred to a complex air combat environment for further training. Experiments have shown that this framework has better transferability and robustness. © 2024 IEEE.

关键词： Reinforcement learning

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Study on the Stability of YIG Crystal Magneto-Optical Sensor Under Small Magnetic Field 19th

Study on the Stability of YIG Crystal Magneto-Optical Sensor...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Li, Qifan Wen, Tao Zhao, Yi School of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

ISBN: (纸本)9789819613786

The optical magnetic field sensor has the characteristics of small size, light weight, good insulation characteristics and has a wide application prospect in the field of magnetic field detection. In the research, it is found that the stability of magneto-optical crystal in small magnetic field is poor, and there are obvious fluctuations, which seriously affects the magneto-optical sensing performance. In order to study the sensing characteristics of magneto-optical crystals in a small magnetic field, this paper establishes a model of crystal magnetization from the perspective of microscopic magnetic domains, and analyzes the magnetization process of the crystal. Finally, this paper proposes a method to improve the sensing performance of the crystal in a small magnetic field by adding a bias magnetic field. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Yttrium iron garnet

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Crowd Counting Algorithm for Train Carriages Based on Convolutional Neural Network 4

Crowd Counting Algorithm for Train Carriages Based on Convol...

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4th International Conference on Computer Science, Electronic Information engineering and Intelligent Control Technology, CEI 2024

作者： Zhang, Ming Zuo, Jing School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou China

ISBN: (纸本)9798350378542

In order to monitor the crowded condition in the carriages and provide accurate data support for urban rail transportation, This study presents a crowd counting approach based on convolutional neural networks for train carriages. The algorithm is based on part of the structure of the VGG-16 network for the initial extraction of passenger features. Through the multi-level information aggregation module, it realizes the enhancement of perception and extraction ability of passenger features at different scales. And by constructing the multi-attention collaboration module, the network pays more attention to the human head region and reduces the interference of background objects. The experimental findings indicate that the proposed algorithm attains a mean absolute error of 1.5 and a mean square error of 2.1, respectively, in the urban rail transit train compartment scenario, suggesting that the proposed algorithm demonstrates high accuracy. © 2024 IEEE.

关键词： Mean square error

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