检索结果-内蒙古大学图书馆

35th International Conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Draženović, Karla Perić, Ante Jakopović, Željko Šunde, Viktor Department of Electric Machines Drives and Automation University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

This paper presents a predictive control approach for controlling the output voltage of an LLC resonant converter. The half-bridge LLC converter is used as a DC battery charger in a solar powered charging station for electric bicycles. The LLC resonant converter was selected for this application due to its inherent soft switching, high efficiency, ability to operate at high switching frequencies, and has a relatively wide voltage range. The predictive control algorithm provides regulation of the output voltage to the set point. The switches of the converter are controlled directly, i.e. without using a modulator which implies a variable switching frequency. ©2021 IEEE.

关键词： Electric bicycle First harmonic approximation LLC resonant converter Predictive control Solar-powered charging station

来源：评论

学校读者我要写书评

暂无评论

Influence of Rotational Speed on the Frequency Response Analysis of the Field Winding of Large Hydrogenerators

Influence of Rotational Speed on the Frequency Response Anal...

引用

IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)

作者： Unai Albizuri-Txurruka José M. Guerrero Kumar Mahtani Carlos A. Platero Engineering Department GE Renewable Energy Bilbao Spain Electronic and Computing Department Mondragon University Arrasate/Mondragon Spain Automation Electrical and Electronic Engineering and Industrial Informatics Department Universidad Politécnica de Madrid Madrid Spain

Frequency Response Analysis (FRA) is a well-known technique used for power transformer condition monitoring for more than 40 years. Some research lines use this technique in other machines such as synchronous machines. This paper presents onsite tests on the field winding of a 125 MVA synchronous machine installed in a pumped storage power plant. The tests have been accomplished in standstill and rated speed conditions. The main contribution of this article is to demonstrate that the speed of the rotor has a significant influence on the field winding FRA test results. A comparison between standstill condition and rated speed FRA tests is presented. The frequency range where the differences take place indicates that centrifugal forces at rated speed change the capacitance of the field windings.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Three-Phase SRF PLL Model for System Frequency Response Studies in Low-Inertia Systems

Three-Phase SRF PLL Model for System Frequency Response Stud...

引用

IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

作者： Matej Krpan Igor Erceg Igor Kuzle Hrvoje Pandžić Department of Energy and Power Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Department of Electric Machines Drives and Automation University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9798350399677

This paper derives a small-signal model of a three-phase synchronous reference frame phase-locked loop for use in system frequency response studies assuming a system of balanced three-phase voltages. The small-signal model is described by a second-order transfer function which relates the actual to the estimated grid frequency. The small-signal model behaves identically to the large-signal model for small disturbances. Simulation results demonstrate that phase-locked loop dynamics can be neglected in the high-inertia scenarios, while in the low-inertia scenarios they have a significant impact on the grid frequency and should be included in models.

关键词： Analytical models Time-frequency analysis System dynamics Power system dynamics Asia Transfer functions Frequency response

来源：评论

学校读者我要写书评

暂无评论

Test-Time Training-Free Domain Adaptation 48

Test-Time Training-Free Domain Adaptation

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Feng, Yongxiang He, Weihua You, Kaichao Liu, Bing Zhang, Ziyang Wang, Yaoyuan Li, Minglei Lou, Yihang Li, Jiawei Li, Guoqi Liao, Jianxing Huawei Technologies Co. Ltd. Advanced Computing and Storage Lab China Peking University School of Electronics Engineering and Computer Science China Huawei Technologies Co. Ltd. Language & Speech Innovation Lab China Huawei Technologies Co. Ltd. GoTen AI Lab Department of Intelligent Vision China Huawei Technologies Co. Ltd. Department of Production Automation Development China Chinese Academy of Sciences Institute of Automation China

ISBN: (纸本)9781728163277

Deploying deep learning models to new environments is very challenging. Domain adaptation (DA) is a promising paradigm to solve the problem by collecting and adapting to unlabeled data in new environments. Though research efforts have led to steady performance improvement over the past decade, DA algorithms are still hard to deploy, as training on unlabeled new data makes tuning difficult and not feasible for inference-only devices. To make DA practical, in this paper we study a new problem named Test-time Training-Free Domain Adaptation (TTDA), where trained models must adapt to a single input (mimicking the test-time scenario) without training. By exploiting spatial activation that was previously overlooked and simply averaged out, we propose a simple method based on Feature Statistics Transformation (FST) on-the-fly for each test example. The proposed algorithm is tested in the TTDA setting on two standard DA benchmarks. Surprisingly, it surpasses or performs on par with state-of-the-art DA methods, even though they require additional training. We envision that this training-free paradigm has the potential to bring DA to embedded devices and would be of interest to audience of community. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning

arXiv

引用

arXiv 2025年

作者： Wang, Hanxuan Lu, Na Zhao, Xueying Yan, Yuxuan Ma, Kaipeng Keong, Kwoh Chee Carneiro, Gustavo Department of Automation Science and Engineering Xi’an Jiaotong University China School of Electrical Engineering Xi’an Jiaotong University China College of Computing and Data Science Nanyang Technological University Singapore Centre for Vision Speech and Signal Processing University of Surrey United Kingdom

Learning from noisy labels (LNL) aims to train high-performance deep models using noisy datasets. Meta learning based label correction methods have demonstrated remarkable performance in LNL by designing various meta label rectification tasks. However, extra clean validation set is a prerequisite for these methods to perform label correction, requiring extra labor and greatly limiting their practicality. To tackle this issue, we propose a novel noisy meta label correction framework STCT, which counterintuitively uses noisy data to correct label noise, borrowing the spirit in the saying "Set a Thief to Catch a Thief". The core idea of STCT is to leverage noisy data which is i.i.d. with the training data as a validation set to evaluate model performance and perform label correction in a meta learning framework, eliminating the need for extra clean data. By decoupling the complex bi-level optimization in meta learning into representation learning and label correction, STCT is solved through an alternating training strategy between noisy meta correction and semi-supervised representation learning. Extensive experiments on synthetic and real-world datasets demonstrate the outstanding performance of STCT, particularly in high noise rate scenarios. STCT achieves 96.9% label correction and 95.2% classification performance on CIFAR-10 with 80% symmetric noise, significantly surpassing the current state-of-the-art. © 2025, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models 38

FIRE: A Dataset for Feedback Integration and Refinement Eval...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Li, Pengxiang Gao, Zhi Zhang, Bofei Yuan, Tao Wu, Yuwei Harandi, Mehrtash Jia, Yunde Zhu, Song-Chun Li, Qing Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology China State Key Laboratory of General Artificial Intelligence BIGAI China State Key Laboratory of General Artificial Intelligence Peking University China Department of Electrical and Computer System Engineering Monash University Australia Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University China Department of Automation Tsinghua University China

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deepwalk-aware graph convolutional networks

引用

Science China(Information Sciences) 2022年第5期65卷 81-95页

作者： Taisong JIN Huaqiang DAI Liujuan CAO Baochang ZHANG Feiyue HUANG Yue GAO Rongrong JI Media Analytics and Computing Lab Department of Computer Science and Technology School of InformaticsXiamen University Media Analytics and Computing Lab Department of Artificial Intelligence School of InformaticsXiamen University School of Automation Science and Electrical Engineering Beihang University Tencent Youtu Lab School of Software Tsinghua University

Graph convolutional networks(GCNs) provide a promising way to extract the useful information from graph-structured data. Most of the existing GCNs methods usually focus on local neighborhood information based on specific convolution operations, and ignore the global structure of the input data. To extract the latent representation for the graph-structured data more effectively, we introduce a deepwalk strategy into GCNs to efficiently explore the global graph information. This strategy can complement the local neighborhood information of a graph, resulting in the more robust representation for the graph *** fusion of the local neighboring and global structured information of a graph can further facilitate deep feature learning at the output layer of GCNs for node classification. Experimental results show that the proposed model has achieved state-of-the-art results on three benchmark datasets including Cora, Citeseer,and Pubmed citation networks.

关键词： graph convolutional networks global information fusion node classification

来源：评论

学校读者我要写书评

暂无评论

Differentially Private Average Consensus with Improved Accuracy-Privacy Trade-off

arXiv

引用

arXiv 2023年

作者： Wang, Lei Liu, Weijia Guo, Fanghong Qiao, Zixin Wu, Zhengguang College of Control Science and Engineering Zhejiang University Hangzhou China Department of Automation Zhejiang University of Technology Hangzhou China Shanghai Institute of Computing Technology Shanghai China

This paper studies the average consensus problem with differential privacy of initial states, for which it is widely recognized that there is a trade-off between the mean-square computation accuracy and privacy level. Considering the trade-off gap between the average consensus algorithm and the centralized averaging approach with differential privacy, we propose a distributed shuffling mechanism based on the Paillier cryptosystem to generate correlated zero-sum randomness. By randomizing each local privacy-sensitive initial state with an i.i.d. Gaussian noise and the output of the mechanism using Gaussian noises, it is shown that the resulting average consensus algorithm can eliminate the gap in the sense that the accuracy-privacy trade-off of the centralized averaging approach with differential privacy can be almost recovered by appropriately designing the variances of the added noises. We also extend such a design framework with Gaussian noises to the one using Laplace noises, and show that the improved privacy-accuracy trade-off is preserved. © 2023, CC BY-NC-SA.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors

引用

Computers, Materials & Continua 2021年第8期68卷 2771-2790页

作者： Izzat Al-Darraji Morched Derbali Houssem Jerbi Fazal Qudus Khan Sadeeq Jan Dimitris Piromalis Georgios Tsaramirsis Department of Automated Manufacturing University of BaghdadBaghdadIraq Department of Mechanical Engineering University of KirkukIraq Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Industrial Engineering College of EngineeringUniversity of Ha’ilHail1234Saudi Arabia Department of Computer Science&IT University of Engineering&Technology PeshawarPakistan Department of Automation University of West AtticaAthensGreece Abu Dhabi Women’s College Higher Colleges of TechnologyAbu DhabiUAE

The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation *** UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle *** the correct components is a critical part of the design ***,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and *** example,satellite-based navigation components should be avoided when designing indoor *** them in the design brings no added value to the final product and will simply lead to increased cost and power *** issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar *** aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout *** paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given *** selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.

关键词： UAV navigation sensors selection UAV navigation autonomous navigation UAV development navigation sensors study navigation systems mapping systems obstacle-avoidance systems

来源：评论

学校读者我要写书评

暂无评论

BiRP: Learning Robot Generalized Bimanual Coordination Using Relative Parameterization Method on Human Demonstration

BiRP: Learning Robot Generalized Bimanual Coordination Using...

引用

IEEE Conference on Decision and Control

作者： Junjia Liu Hengyi Sim Chenzui Li Kay Chen Tan Fei Chen Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong SAR Department of Computing The Hong Kong Polytechnic University Hong Kong SAR

Human bimanual manipulation can perform more complex tasks than a simple combination of two single arms, which is credited to the spatio-temporal coordination between the arms. However, the description of bimanual coordination is still an open topic in robotics. This makes it difficult to give an explainable coordination paradigm, let alone applied to robotics. In this work, we divide the main bimanual tasks in human daily activities into two types: leader-follower and synergistic coordination. Then we propose a relative parameterization method to learn these types of coordination from human demonstration. It represents coordination as Gaussian mixture models from bimanual demonstration to describe the change in the importance of coordination throughout the motions by probability. The learned coordinated representation can be generalized to new task parameters while ensuring spatio-temporal coordination. We demonstrate the method using synthetic motions and human demonstration data and deploy it to a humanoid robot to perform a generalized bimanual coordination motion. We believe that this easy-to-use bimanual learning from demonstration (LfD) method has the potential to be used as a data augmentation plugin for robot large manipulation model training. The corresponding codes are open-sourced in https://***/Skylark0924/Rofunc.

关键词：

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：