检索结果-内蒙古大学图书馆

2023 International Conference on Power Energy Systems and Applications, ICoPESA 2023

作者： Ye, Jian Mei, Sen Guo, Huanyu Hu, Yingjie Zhang, Xinan Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China University of Western Australia School of Electrical Electronic and Computer Engineering Perth Australia

ISBN: (纸本)9798350345605

This paper proposes a DC-AC inverter controller based on reinforcement learning (RL) algorithm. Compared with the traditional PID control method, the structure of the RL algorithm based controller is simpler. The deep deterministic policy gradient (DDPG) algorithm in RL algorithm is used to realize model-free control of inverters, so that the control algorithm has adaptive ability to different types of DC-AC inverters. It can avoid the dependence of the control strategy on the system model. Through simulation, the control strategy of three-phase two-level DC-AC inverter based on DDPG algorithm is compared with the traditional PID control. The simulation results show that the total harmonic distortion (THD) is reduced by 12% and the current tracking performance is improved by at least 75%. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Simulation of non-inductive vector control of permanent magnet synchronous motor based on sliding mode observer 3

Simulation of non-inductive vector control of permanent magn...

引用

3rd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Zhang, Caiyue Liu, Zipin Xu, Bowen Guilin University of Electronic Technology School of Electronic Engineering and Automation Guilin China Xi'An University of Science and Technology School of Electrical and Control Engineering Shaanxi Xi'an China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350398410

Permanent magnet synchronous motors (PMSM) are widely used due to their numerous benefits. It is critical to get rotor position and speed information in order to operate the motor accurately. Sensorless control techniques have emerged as a popular study area both at home and overseas. The sliding mode observer (SMO) may indirectly detect rotor position and has the benefits of easy implementation and efficient algorithms. In this study, a mathematical model for sensorless control of a PMSM is developed using SMO, vector control, and other techniques. With a surface-mounted PMSM as the study object, a mathematical model for sensorless control of PMSM is developed. PMSM's sliding mode observer model is built in the matlab/simulink environment. Experiments demonstrate that the system can track the rotor position and speed of the motor precisely and fulfill the requirements of sensorless vector control of PMSM. © 2023 IEEE.

关键词： Sensorless control

来源：评论

学校读者我要写书评

暂无评论

Resource Allocation and Trajectory Optimization in Unmanned Aerial Vehicle-assisted Mobile Edge Computing

Resource Allocation and Trajectory Optimization in Unmanned ...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Cheng, Xiangshuai Yuan, Haitao Niu, Siyu Zhai, Jiahui College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

Edge computing offers a groundbreaking architecture for supplying computing, storage, and networking resources to propel the Internet of Things forward. By situating them at the network's edge, this model makes computational power more accessible to users. If tasks are executed entirely at the edge, energy and resource constraints of edge nodes may lead to poor performance. Therefore, it is widely recognized that offloading certain tasks to cloud data centers (CDCs), which possess abundant execution resources, is advantageous. However, implementing CDCs is not widespread and lacks flexibility in isolated regions. This presents challenges and high costs for reliably completing tasks quickly. Consequently, employing more adaptable unmanned aerial vehicles (UAVs) as CDCs in specific scenarios is crucial. The work presents the idea of mobile edge computing supported by the UAV. By considering the needs of user services, we enhance the energy efficiency of the UAV by optimizing their trajectories, transmission power, and computational load distribution. Furthermore, the work introduces an improved algorithm called GeneticSimulated-annealing-based Particle Swarm Optimizer (GSPSO) to optimize the energy efficiency of the UAV. Experimental simulations show that regarding the energy efficiency of the UAV, GSPSO exhibits superior search efficiency, surpassing genetic algorithm, simulated annealing, and particle swarm optimization by 7.39%, 15.03%, and 27.93%, respectively. © 2024 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Water Quality Anomaly Detection with Dual Sliding Windows and Convolutional LSTM

Water Quality Anomaly Detection with Dual Sliding Windows an...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Yuan, Ming Yuan, Haitao Wang, Ziqi Qiao, Junfei College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

Water pollution is continuously increasing in water ecosystems across all continents. Surface water sensors can record data on water quality indicators at regular intervals, and the associated water quality sequences show abnormal trends when extreme weather or unusual industrial discharges occur. Therefore, governments can take timely actions to minimize damage and protect the water environment by detecting these abnormal trends promptly. However, current methods make it difficult to interpret different correlations among water quality parameters effectively. To solve this problem, this work proposes a parameter correlation-aware anomaly detection model, which integrates Dual sliding windows, Convolutional LSTM, and a Deep neural network with dropout, called for DCLD short. First, DCLD designs dual sliding windows to capture local and global patterns within the sequence of water quality. Second, DCLD adopts a stacked long short-term memory with a convolutional neural network to capture complex features and long-term dependencies in the time series. Third, DCLD uses a deep neural network incorporating the dropout algorithm to extract abstract features. DCLD mitigates overfitting risks and enhances the model's generalization capacity. Finally, DCLD is evaluated with two real-world water quality datasets, and its anomaly detection accuracy is improved by 5.41% and 0.79% on average over its peers. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A monocular 3D human pose estimation approach for virtual character skeleton retargeting

引用

Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9563-9574页

作者： Yang, Aolei Liu, Guancheng Naeem, Wasif Wu, Dakui Zhou, Yinghong Chen, Ling School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Northern Ireland BelfastBT7 1NN United Kingdom School of Engineering and Design Hunan Normal University Changsha410081 China

This paper presents a monocular 3D human pose estimation approach for virtual character skeleton retargeting with monocular visual equipment. First, the 2D human pose is achieved by using the OpenPose method from the continuous video frames collected by the monocular camera, and the corresponding 3D human pose is estimated by fusing and constructing the depth-channel pose estimation network. The pose filter network is next designed to smooth and optimize the 3D human pose estimation through a sliding window strategy. The human pose skeleton retargeting and optimizer methods are then proposed to support video motion capture applications and virtual character skeleton retargeting for animation based on the bone direction vectors and the re-projection error of joint points. Finally, the performance of the proposed approach is verified on Human3.6 M dataset, and the results show that the mean per-joint position error in the public dataset is 40.5 mm, which is lower than that of the multiple benchmark methods. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A New Configuration for Waveguide Filters With Parallel Coupling Paths 15

A New Configuration for Waveguide Filters With Parallel Coup...

引用

15th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2023

作者： Wu, Weijun Guo, Zai-Cheng Zhu, Lei Nanjing Normal University School of Electrical and Automation Engineering Nanjing210046 China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering 999078 China

ISBN: (纸本)9798350338874

A new configuration is proposed for filters with parallel coupling paths between the source and load in this paper. The proposed fourth-order waveguide bandpass filter (BPF) with two parallel coupled paths is formally designed through this structure. The filter is working at 6.5 GHz and with 300 MHz bandwidth. Due to the two parallel coupling paths, a pair of transmission zeros (TZs) are generated out of passband. Compared with previous waveguide filters, the coupling paths are connected to the source and load in different sides of input/output waveguide. In this way, the waveguide cavity of the resonator can be increased and the insertion loss of the filter can be greatly reduced. The effectiveness of the fourth-order waveguide bandpass filter is verified by simulation results. © 2023 IEEE.

关键词： Bandpass filters

来源：评论

学校读者我要写书评

暂无评论

A Deep Deterministic Policy Gradient Algorithm Based controller with Adjustable Learning Rate for DC-AC Inverters 2

A Deep Deterministic Policy Gradient Algorithm Based Control...

引用

2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Ye, Jian Mei, Sen Guo, Huanyu Zhao, Di Zhang, Xinan School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Electrical Electronic and Computer Engineering University of Western Australia Perth Australia

ISBN: (纸本)9798350313765

This paper proposes an inverter control algorithm based on the deep deterministic policy gradient (DDPG) with adjustable learning rates. This algorithm retains the advantages of model-free control of the inverter and solves the inherent problem of learning rate setting in deep neural networks. As a result, the control algorithm can quickly converge to the desired state during training, accelerate the training process, and not be affected by the control effect. Through simulation, the training results of the adjustable learning rate DDPG algorithm are compared with those of the constant small learning rate and constant large learning rate DDPG algorithms. The simulation results show that the training efficiency is improved by 75%, while the control effect on the inverter is almost unaffected. © 2023 IEEE.

关键词： deep deterministic policy gradient algorithm learning rate reinforcement learning Three-Phase DC-AC Inverters

来源：评论

学校读者我要写书评

暂无评论

Graph Attention Transformer with Dilated Causal Convolution and Laplacian Eigenvectors for Long-term Water Quality Prediction

Graph Attention Transformer with Dilated Causal Convolution ...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Chen, Danqing Yuan, Haitao College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

Water quality prediction has emerged as a prominent research problem in recent years, which entails a spatiotemporal prediction task. However, several challenges are associated with water quality prediction: 1) water quality time series exhibit complex nonlinear relationships, making prediction challenging;2) water quality sensors are distributed across river networks, leading to strong spatial dependencies in water quality prediction;3) current methods like traditional machine learning methods have poor accuracy in long-term water quality prediction. To solve these problems, this work proposes a spatiotemporal prediction model named Graph Attention Transformer with Dilated Causal Convolution and Laplacian Eigenvectors (GTDL). First, dilated causal convolution is adopted to extract temporal features of input sequences. Second, a transformer with Laplacian eigenvectors is designed to extract spatial dependencies of river networks. Third, residual connections are utilized at the output stage to enhance the accuracy of the long-term prediction. Finally, GTDL is evaluated with two real-world water quality datasets and experimental results prove that GTDL outperforms other baseline methods regarding the prediction accuracy. Specifically, compared with five state-of-the-art prediction models, GTDL improves the prediction accuracy by 11.3%-63.5% and 6%-52.4% on two datasets, respectively. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

A Novel Multimodal Humanoid Robot control System Framework Design Based on SSVEP-BCI and Eye-Tracking 7

A Novel Multimodal Humanoid Robot Control System Framework D...

引用

7th International Conference on Biological Information and Biomedical engineering, BIBE 2024

作者： Han, Chunxiao Hu, Yue Liu, Yanli Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9783800762910

As population ageing increases, Brain-computer Interface (BCI) technology combined with humanoid robots has become an innovative solution to alleviate the stress of elderly care. To improve the reliability and stability of the BCI system in practical applications, this paper proposed a novel multimodal humanoid robot control system. There are two different control modalities in parallel: Steady State Visual Evoked Potential (SSVEP)-BCI control modality and Eye Tracking control modality. The system utilized blinks events enable the user to initiate the human-machine interface (HMI) autonomously, selected one of the control modes based on the user's attention state, and sent control commands to the robot for execution. This multimodal framework effectively solves the false triggering problem of the humanoid BCI system, and the humanoid robot can perform tasks more flexibly. © VDE VERLAG GMBH.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

Enhanced Potato Detection Using an Improved YOLOv8 Algorithm 24

Enhanced Potato Detection Using an Improved YOLOv8 Algorithm

引用

9th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2024

作者： Wang, Zihan Zhang, Yunxi Ma, Yuqi Zhao, Ya Liu, Jia School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798400716911

This paper proposes a novel potato detection algorithm YOLOv8-P, based upon the improved YOLOv8 framework to achieve enhanced detection accuracy. The algorithm incorporates the BiFormer attention mechanism and introduces an additional detection layer specifically designed for large targets, thereby significantly improving the model's performance in identifying larger potatoes. Additionally, a comprehensive dataset named potato-2024 was developed to address the limitations of existing public datasets in potato detection. To validate the effectiveness of YOLOv8-P, comparative experiments were conducted with YOLOv5 and YOLOv8 on the potato-2024 dataset. The results demonstrate that, under identical experimental conditions and parameters, YOLOv8-P exhibits superior recognition accuracy in potato identification, thus establishing a new benchmark in potato detection technology. © 2024 Copyright held by the owner/author(s).

关键词： YOLOv8

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：