检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Che, Hao-Chi Wu, Huai-Ning School of Automation Science and Electrical Engineering Beihang University Beijing China The Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Hangzhou International Innovation Institute Beihang University Hangzhou311115 China

In this paper, the coordinated control problem of deformation and flight for morphing aircraft (MA) is studied by using meta-learning (ML) and coupled state-dependent Riccati equations (CSDREs). Our method is built on two principal observations that dynamic models of MA under varying morphing conditions share a morphing condition independent representation function and that the specific morphing condition part lies in a set of linear coefficients. To that end, the domain adversarially invariant meta-learning (DAIML) is employed to learn the shared representation with offline flight data. Based on the learned representation function, the coordinated control of the deformation and flight for MA is formulated as a non-cooperative differential game. The state-dependent feedback control solutions can be derived by addressing a pair of CSDREs. For this purpose, Lyapunov iterations are extended to obtain the positive semidefinite (definite) stabilizing solutions of the CSDREs, and the convergence proof of the proposed algorithm is provided. Finally, a simulation study is carried out to validate the efficacy of the developed coordinated game control strategies. Copyright © 2025, The Authors. All rights reserved.

关键词： Riccati equations

来源：评论

学校读者我要写书评

暂无评论

Development of a PM Spherical Actuator with Tiltable Stator for High Torque Density

引用

IEEE Transactions on Transportation Electrification 2025年

作者： He, Xinghua Xiang, Pengjie Yan, Liang Yang, Xuxu Liu, Xiaoshuai Du, Nannan Bu, Suwan Yan, Guishan Ai, Chao Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Ningbo Institute of Technology Ningbo315800 China Sun Yat-Sen University School of Intelligent Systems Engineering Shenzhen518000 China Yanshan University School of Mechanical Engineering Qinhuangdao066004 China

Spherical actuators are active joints that rotate around three directions and are more compact than conventional joints using multiple single-axis motors connected in series. However, spherical electromagnetic actuators have low torque density, particularly in tilt directions, hindering practical applications. The essential reason is that their stator and rotor are misaligned after tilting, which not only reduces the electromagnetic torque but also introduces restoring torques. To enhance torque density, this paper proposes a 3-DOF permanent magnet spherical actuator with a tiltable stator. The relative positions of the stators and rotors of each actuation unit remain unchanged after tilting, maintaining high output torque and allowing large tilting angles, and rotating and tilting torques are decoupled. We introduce the working principle of the proposed actuator and establish its basic structure. Two-dimensional magnetic field finite element analysis and conformal transformation are combined to simplify three-dimensional magnetic field computations. The optimized parameters for the tilting unit are obtained. Finally, a prototype is fabricated and experimentally tested. The proposed spherical actuator yields a tilt torque exceeding 8 Nm and a rotation torque of 7.34 Nm, corresponding to a torque density of 1.75 Nm/kg for tilt and 1.6 Nm/kg for rotation relative to the entire actuator. © 2015 IEEE.

关键词： Spheres

来源：评论

学校读者我要写书评

暂无评论

Research on Attack Detection Method for V2V System Based on Multi-dimensional Taylor Series Expansion Framework

引用

IEEE Sensors Journal 2025年第11期25卷 19576-19591页

作者： Wang, Di Wen, Chenglin Liu, Weifeng Shaanxi University of Science and Technology School of Electrical and Control Engineering Xi’an710021 China Guangdong University of Petrochemical Technology Department of Automation Maoming525000 China

Strongly stealthy cyber-attacks in networked vehicle queue (V2V) network environments often manifest themselves as small changes to data, which makes it difficult for existing methods to effectively detect such attacks. Although the initial impact of these attacks is minimal, they are capable of significantly disrupting the system over time. To address this issue, this paper proposes a new data representation model for attack detection, aiming to overcome the limitations of existing detection methods. For subtle and persistent attack features, we present a multi-level data representation framework, which enables effective comparison of attack features at different scales by extracting features at various levels. Through hierarchical processing of features, these subtle changes are revealed at the micro level, thereby enhancing the system’s sensitivity to stealthy attacks. The experimental results show that the method in this paper can effectively detect the covert false data injection (FDI) attacks. Meanwhile, we compared the proposed method with the most recent competing methods, and the results demonstrated that our method has higher detection accuracy and stronger robustness compared with the existing methods (Figure presented). © 2001-2012 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

An Advanced Deep Learning Detection of Rice Plant Diseases Based on Residual Neural Networks 8th

An Advanced Deep Learning Detection of Rice Plant Diseases B...

引用

8th International Conference on Advances in Computing and Data sciences, ICACDS 2024

作者： Huong, Nguyen Thanh Lan, Nguyen Dang Dong, Trinh Cong Thanh, Bui Dang School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Viet Nam Institute for Control Engineering and Automation Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9783031709050

For countries with the large rice export in the world, taking care of rice plants for them to grow healthily is very necessary. One of the techniques is to detect diseases promptly, at the right time, on the right diseases in order that necessary treatment can be taken to minimize the harmful effects of diseases on rice plants as well as prevent them from breaking out into epidemics. Previously, disease detection was carried out manually, which took a lot of time and labor. Nowadays, automated methods have been increasingly applied for precision agriculture applications. In the article, a method to automatically detect rice diseases based on machine learning, especially deep learning concentrated method is proposed. In this article, our study concentrates on detecting four most common rice diseases: brown spot, hispa, blast and blight. The dataset for training, testing and validation collected and constructed from Kaggle and Google dataset includes approximately 400 images for each type of rice leaf diseases. From the experiment to assess the performance of the proposed learning method, the accuracy can reach approximately 97%. Thereby, the method shows feasibility and reasonableness, with extensively potential usage for practical precision agriculture application. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Online Learning-Based Predictive control for Nonlinear System

arXiv

引用

arXiv 2025年

作者： Zhang, Yuanqing Zhang, Huanshui School of Control Science and Engineering Shandong University Shandong Jinan250061 China College of Electrical Engineering and Automation Shandong University of Science and Technology Shandong Qingdao266590 China

In this paper, we propose an online learning-based predictive control (LPC) approach designed for nonlinear systems that lack explicit system dynamics. Unlike traditional model predictive control (MPC) algorithms that rely on known system models to optimize controller outputs, our proposed algorithm integrates a reinforcement learning component to learn optimal policies in real time from the offline dataset and real-time data. Additionally, an optimal control problem (OCP)-based optimization framework is incorporated to enhance real-time computational efficiency while ensuring stability during online operation. Moreover, we rigorously establish the super-linear convergence properties of the algorithm. Finally, extensive simulations are performed to evaluate the feasibility and effectiveness of the proposed approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

SGDR-YOLOv8: Training Method for Rice Diseases Detection Using YOLOv8 8th

SGDR-YOLOv8: Training Method for Rice Diseases Detection Usi...

引用

8th International Conference on Advances in Computing and Data sciences, ICACDS 2024

作者： Thanh, Bui Dang Anh, Mac Tuan Khanh, Giap Dang Dong, Trinh Cong Huong, Nguyen Thanh School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Viet Nam Institute for Control Engineering and Automation Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9783031709050

In Vietnam, rice stands as a vital food source for the whole population, and because of that timely identification and management of rice plant diseases is extremely crucial. Among the diseases that appear in Vietnam, blast leaf, leaf folder, and brown spot are among the most prevalent ailments that harm rice plants, directly impacting cultivation. To address this problem, deep learning, a cutting-edge solution can be used to detect plant diseases. In this paper, we present an approach utilizing Deep learning to identify illnesses affecting rice leaves. YOLOv8 is employed and trained with various strategies of Stochastic Gradient Descent with Warm Restart (SGDR) to identify diseases on rice leaves. The result of the proposed method is assessed using 309 images. The experimental findings reveal an accuracy of 88.6%, indicating superior performance compared to alternative methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Plant diseases

来源：评论

学校读者我要写书评

暂无评论

Underwater arbitrary ranging based on chirped pulse interferometry with a mode-locked laser

引用

Journal of Lightwave Technology 2025年第11期43卷 5235-5243页

作者： Shi, Haonan Zhao, Haihan Xu, Xinyang Zhu, Zhiwei Zhai, Jingsheng Li, Xiaobo Tianjin University School of Marine Science and Technology Tianjin300072 China Research Institute of China Electronics Technology Group Corporation Science and Technology on Electro-Optical Information Security Control Laboratory No. 53 Tianjin300308 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong999077 Hong Kong Nanjing University of Aeronautics and Astronautics Key Laboratory of Space Photoelectric Detection and Perception Ministry of Industry and Information Technology Nanjing211106 China

Underwater distance measurement and length sensing, as fundamental functions of geoscience, are integrated into underwater robots and vessels in various forms of sensor payloads and play a crucial role in a wide range of remote sensing applications. Advanced laser-based detection systems and algorithms are essential for underwater tasks, such as detecting damage in underwater pipelines and conducting detailed structural health assessments. In this paper, we experimentally demonstrated an arbitrary underwater ranging system by the chirped pulse interferometry with a mode-locked laser. Water's inherent characteristic introduces dispersion, enabling unique distance discrimination. Adjusting the repetition frequency allows us to acquire the interference spectrum. A long fiber delay line, stabilized by the servo-controlled system, eliminates the ranging dead zone. The widest fringe of the interference spectrum, corresponding to an instantaneous repetition frequency, indicates the arbitrary measured distance. Leveraging a charge-coupled device detection module, we achieved an update rate of 13.5 Hz for the interference spectrum. Experimental results show a precise distance difference within 59.8 μm at the 5 m range underwater without the dead zone. © 2025 IEEE. All rights reserved.

关键词： Laser mode locking

来源：评论

学校读者我要写书评

暂无评论

GGIMN: Gravity Gradient Image Matching Network with Adaptive Adjoint Smoothing for AUV Navigation

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Li, Tianjiao Wang, Bo Song, Bao Deng, Zhihong Fu, Mengyin Beijing Institute of Technology School of Automation Beijing100081 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin300382 China Beijing Institute of Technology Engineering Research Center of the Ministry of Education for Navigation Guidance and Control Technology School of Automation Beijing100081 China Nanjing University of Science and Technology Nanjing210014 China

Gravity gradient-aided navigation is a promising navigation method for autonomous underwater vehicle (AUV), in which matching algorithm is its key technology. Image matching algorithms have higher matching accuracy and information utilization than single point matching and sequence matching. However, the spatial domain image feature matching ability is weak in areas with insignificant feature changes due to the uneven feature distribution in the gravity gradient reference map. To break through this limitation and solve the problem of insufficient spatial domain image feature matching ability, we propose a gravity gradient image matching network (GGIMN) with adaptive adjoint smoothing for AUV navigation and positioning. First, a training set for GGIMN with equal numbers of positive and negative samples is constructed by preparing the gravity gradient reference map and fitting the gravity gradient measured map. Then, the feature extraction part of MatchNet is expanded to construct a deep learning network with five gravity gradient twin towers in parallel. Subsequently, an adaptive adjoint smoothing method that combines the idea of sequence matching is proposed to solve the problem of unsmooth matching trajectory and further improve the matching accuracy. Finally, the GGIMN is trained offline, and the gravity gradient map is matched and positioned online. The results of marine experiments show that the GGIMN has higher matching and positioning accuracy, and the average positioning error is reduced beyond 70% compared with onedimensional matching algorithms such as single-point iteration and sequence matching. © 1967-2012 IEEE.

关键词： Image matching

来源：评论

学校读者我要写书评

暂无评论

A review of axial force balance and clearance sealing techniques for energy-efficient scroll compressors

引用

International Journal of Refrigeration 2025年 176卷 298-321页

作者： Wen, Hui Yan, Ranran Liu, Lei Wu, Yan Chen, Bingtuo Wang, Wenting Qu, Xiao Cai, Jiongjiong School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou310023 China Jiaxipera Compressor Co. Ltd. Jiaxing314006 China Dahua Technology Co. Ltd. Hangzhou310053 China Power Electronics and Machines Control Research Institute University of Nottingham NG7 2GT United Kingdom

Developing next-generation scroll compressors with higher efficiency and reliability is crucial for promoting energy conservation and emission reduction. Among the key technical challenges encountered, radial gas leakage remains a predominant issue that can severely impair both operating performance and energy consumption. This paper begins by elucidating the flow characteristics and estimation methods for radial leakage. The influence mechanisms for radial leakage and the performance effects are then examined in terms of leakage rate, power consumption and scroll surface wear. The unsteady characteristics of axial gas force, which pose a primary challenge to axial clearance sealing, are analyzed through a combination of theoretical analysis, CFD simulation and experimental measurement. Based on this foundation, this paper provides a comprehensive review of key advancements in axial force balance and clearance sealing techniques, including conventional approaches such as gas back-pressure, oil back-pressure, axial compliance and passive aerodynamic sealing mechanisms as well as emerging solutions like passive magnet and active electromagnet mechanisms, with a focus on their principles, topology, effectiveness, and limitations. Finally, the study highlights key insights and unresolved challenges, recommending hybrid electromagnetic mechanisms as a promising solution that combines the advantages of both passive and active dynamic force balancing techniques. © 2025 The Authors

关键词： Scroll compressors

来源：评论

学校读者我要写书评

暂无评论

BnB-Based Robust PnP Pose Estimation Method for Outliers

引用

IEEE Robotics and automation Letters 2025年第7期10卷 6856-6863页

作者： Chenrong Long Qinglei Hu Cuicui Jiang Dongyu Li Zhenchao Ouyang School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Institute of Control Engineering Beijing China Tianmushan Laboratory Hangzhou China Zhongfa Aviation Institute of Beihang University Hangzhou China School of Cyber Science and Technology Beihang University Beijing China

The Perspective-n-Point (PnP). problem is a fundamental issue in the field of computer vision. However, the PnP problem is susceptible to the influence of outliers. In this letter, we introduce a robust PnP pose estimation method based on the Branch and Bound (BnB) algorithm. Considering that the computational complexity of the BnB method is related to the dimensionality of the parameter space, we construct a cost function based on the maximization of the consensus set for the parameter $\bm {R}^{T}\bm {t}$ . This approach reduces the search from a 6D space to a 3D space, thereby decreasing computational complexity and reducing computation time. Subsequently, we derive the upper and lower bounds for the BnB algorithm and perform pruning until convergence to obtain the global optimal solution for this parameter. After identifying corresponding point pairs that meet the inlier threshold, we employ Singular Value Decomposition (SVD) to solve for the translation and rotation parameters from this parameter. Finally, extensive comparative studies across synthetic and real datasets reveal that our method delivers accurate pose estimation and demonstrates robustness against noise and outliers, offering a viable solution for PnP issues in practical applications.

关键词： Pose estimation Iterative methods Accuracy Cost function Three-dimensional displays Noise Translation Robustness Computational complexity Vectors

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：