检索结果-内蒙古大学图书馆

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Li, Daiwei Fu, Li Wang, Lingling Fan, Wenhu Li, Yuan School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Experimental Teaching Demonstration Center of Mechanical and Control Engineering Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

In this paper, a new method of the hardware-in-the-loop (HWIL) simulation test of aircraft guidance, navigation and control (GNC) system is proposed based on cable-driven parallel robot and triaxial turntable. The traditional HWIL simulation test methods of the aircraft GNC system, which depends on the five axes motion platform or the six-degree-of-freedom motion system, have a series of problems such as expensive and complex test equipment, single test mode, and monotonous simulation trajectory. Aiming at the needs of teaching and scientific research, this paper proposes a low-cost and efficient HWIL simulation test scheme for GNC system. Through simulation analysis and verification, the scheme has some advantages over traditional methods in workspace and control accuracy. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hardware-in-the-loop simulation

来源：评论

学校读者我要写书评

暂无评论

Beta Oscillations Suppression in a Population Model of Parkinson's Disease by Linear Delayed Feedback control 37

Beta Oscillations Suppression in a Population Model of Parki...

引用

37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Yang, Jingyu Che, Yanqiu Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781665465366

Parkinson's disease (PD) is the second most prevalent degenerative neurological illness. Beta oscillations in electroencephalogram (EEG) are produced when a patient is suffering from PD. Deep brain stimulation (DBS) is one of the most successful treatments for PD, however, DBS control schemes still need improvement. In this paper, we test linear delay feedback control for DBS targeted the subthalamic nucleus (STN) or the internal globus pallidus (GPi) in a neural computing population model, describing dynamics of the cortex thalamocortical basal ganglia network. The numerical simulations show that both STNDBS and GPI-DBS can efficiently control beta oscillations of the PD state in term of frequency decrease. © 2022 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Lightweight Deep Driver Distraction Recognition Network

Lightweight Deep Driver Distraction Recognition Network

引用

IEEE International Conference on Information Communication and Signal Processing (ICICSP)

作者： Yutian Wu Yaqi Yin Jiaying Wu Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

When the driver shifts his attention away from the driving task and performs behaviors unrelated to driving, it is very easy to slow down the driver's perception ability and cause decision delays. Therefore, timely and accurate identification of driver distraction and issuing of alerts can help improve driving safety. Due to the diverse representations of driver distraction behaviors, it is difficult to collect an dataset which contains all kinds of driver distraction actions to train deep neural networks. This paper proposed an attention-based deep driver distraction recognition neural network DDDNet, which is trained by contrastive learning method to learn to judge complex driving distraction behaviors. Besides, in order to meet the requirement of high processing speed and recognition accuracy, on the basis of the lightweight feature extraction network MobileNetV2, DDDNet proposed to add a three-dimensional channel attention module to strengthen the effective feature. Experimental results show the DDDNet is able to identify a variety of distracting behaviors which it has not met before, with high recognition accuracy of 87.12% and real-time processing speed of 140fps.

关键词： Accuracy Image recognition Contrastive learning Streaming media Signal processing Feature extraction Vectors Real-time systems Safety Driver behavior

来源：评论

学校读者我要写书评

暂无评论

Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

引用

IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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： Long, Chenrong Hu, Qinglei Jiang, Cuicui Li, Dongyu Ouyang, Zhenchao Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beijing Institute of Control Engineering Beijing100094 China Tianmushan Laboratory Hangzhou310023 China Zhongfa Aviation Institute of Beihang University 166 Shuanghongqiao Street Pingyao Town Yuhang District Hangzhou311115 China Beihang University School of Cyber Science and Technology Beijing100191 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 paper, 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 RT 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. © 2016 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Kinematic analysis and dynamics modeling of a novel ball joint actuator with three-degree-of-freedom 11

Kinematic analysis and dynamics modeling of a novel ball joi...

引用

11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Wen, Yan Wang, Yong Li, Guoli Wang, Qunjing Ye, Qiubo Zhang, Qian Xie, Fang Anhui University School of Internet Hefei China Anhui University National Engineering Laboratory of Energy-Saving Motor & Control Technology Hefei China Anhui University School of Electrical Engineering and Automation Hefei China Anhui University Anhui Key Laboratory of Industrial Energy-Saving and Safety Hefei China Jimei University School of Ocean Information Engineering and Automation Xiamen China

ISBN: (纸本)9788957083505

A new ball joint actuator with three-degree-of-freedom is proposed to solve the problem of space motion. It can perform some specific work in a certain space with multiple degrees of freedom. At first, the kinematics and workspace of the actuator are analyzed. Then, the dynamics is analyzed using the LaGrange method. In this paper, a modeling approach from the serial robotic arm is utilized to derive a symmetric, positive definite inertia matrix. It facilitates easier access to the dynamical model. Finally, simulation analysis is performed to verify the effectiveness of the method. © 2023 The Korean Institute of Power Electronics.

关键词： Kinematics

来源：评论

学校读者我要写书评

暂无评论

Blockchain-based Data Integrity and Privacy Protection Method for Swarm Robotics 17th

Blockchain-based Data Integrity and Privacy Protection Metho...

引用

17th Chinese Intelligent Systems Conference, CISC 2021

作者： Li, Bangyin Chen, Yutao Zuo, Zhiqiang Huang, Jie School of Electrical Engineering and Automation Fuzhou University Fuzhou350108 China School of Electrical and Information Engineering Tianjin University Tianjin300072 China Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350108 China

ISBN: (纸本)9789811663192

Swarm robotics realize collaboration through information interaction among robots. One of the key aspects of stable and reliable operation of swarm robotics is protecting the privacy and content of the interactive data. Blockchain has been traditionally applied to digital currency due to its decentralization and high security features. Since robots can serve as a node in blockchain, and both swarm robotics and blockchain share the distributed architecture, there is great potential to apply blockchain technology to ensure the security of interactive data in swarm robotics. In this paper, a brief review of the current studies on the applying blockchain to swarm robotics is given. In addition, a blockchain data protection method is employed to protect the data integrity and privacy of swarm robotics. Finally, a simulation using the swarm robotics simulator and the Ethereum blockchain test network is conducted. Results demonstrate the effectiveness of the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Photovoltaic Power Prediction of Meteorological Based on Data Drive and Mechanism Model

Photovoltaic Power Prediction of Meteorological Based on Dat...

引用

第35届中国控制与决策会议

作者： Shanna Luo Kaixiang Peng Changbin Hu Xuecheng Li School of Automation and Electrical Engineering University of Science and Technology Beijing School of Electrical and Control Engineering North China University of Technology

The proportion of photovoltaics(PV) in the grid has increased significantly with the extensive use of renewable ***,natural factors such as weather have a great influence on the output power of *** by the randomness and volatility of PV output power,there are unpredictable power disturbances,which can easily cause a mismatch between PV output and load demand,resulting in bus voltage fluctuations,thereby affecting the safety and stability of the *** PV power prediction models usually directly uses the data characteristics such as horizontal solar radiation flux and temperature in the meteorological forecast,ignoring the effect of solar angle on power *** order to further improve the accuracy of PV power prediction,a prediction method based on the meteorological data driven and mechanism integration is ***,the influence mechanism of solar angle on power prediction is analyzed using the solar radiation bevel conversion principle,and the solar angle solving model is ***,the meteorological forecast data is expanded on the basis of the solar angle mechanism the point forecast and the trend forecast models are established,and the prediction results are fused with the error ***,through the test of different prediction time standards for 1 day,3 days,and 7 days of the data of multiple real light fields,the effectiveness of the method proposed in this article was verified.

关键词： Solar Angle NWP weather forecast combination forecast Data Drive Mechanism Model

来源：评论

学校读者我要写书评

暂无评论

Tracking performance limitations of networked control systems with packet dropouts and logarithmic quantization 41

Tracking performance limitations of networked control system...

引用

第41届中国控制会议

作者： Jianhao Li Xiaowei Jiang Hao Chen Shaoying Wang Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System College of Science Binzhou University School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we focus on the tracking performance(TP) limitations of networked control systems(NCS s).The control system considered is a multi-input and multi-output(MIMO) discrete-time network control system with time delay,channel noise,packet dropouts,and logarithmic quantization communication *** modeling the channel,we assumed the channel noise to be additive white Gaussian noise(AWGN) and used a binary random process to model packet dropouts and a logarithmic quantizer to model the quantization *** explicit expression of the TP limitations of NCSs utilizing the two-degree-of-freedom(TDOF) controller is then derived using the frequency-domain approach,coprime decomposition,and Youla parameterization *** results show that the essential characteristics of the plant(locations and directions of nonminimum phase zeros and unstable poles) and network constraints(time delay,packet dropouts,quantization,and noise power spectral density) are closely related to the TP limitations.

关键词： Networked control systems tracking performance limitations packet dropouts logarithmic quantization

来源：评论

学校读者我要写书评

暂无评论

EBD-YOLO：a lightweight auxiliary driving detection algorithm based on YOLOv5

引用

Optoelectronics Letters 2025年

作者： SUN Lianshuai SHI Tao DING Yao LI Song Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems， School of Electrical Engineer-ing and Automation， Tianjin University of Technology College of Electrical Engineering， North China University of Science and Technology

A lightweight road-assistant detection algorithm， EBD-YOLO， based on YOLOv5s is proposed to address the problems of high model complexity， computation cost， and difficulty in deployment on resource-limited embedded terminals in existing assisted driving detection algorithms. First， lightweight Transformer model EfficientViT was used as the backbone feature extraction network of YOLOv5s model to reduce network parameters and calculation costs. Secondly， a Focal-GIoU Loss function is proposed for bounding box regression to accelerate model convergence and reduce loss. Thirdly， the feature pyramid structure is improved to a weighted bi-directional feature pyramid network (BiFPN) to enhance localization and semantic features. Then， a dynamic head framework is added to unify the attention mechanism with the object detection head to improve its performance. Finally， a Soft-CIoU＿NMS algorithm is proposed in the post-processing stage to enhance occluded targets' localization and detection ability and reduce the missed detection rate. We conducted experiments on the KITTI and BDD100K datasets for autonomous driving， and the results showed that the EBD-YOLO model reduced in size by 38.4% and 37.2%， respectively. In comparison， the computational cost was reduced by 48.1%. As measured by mAP@0.5， the detection accuracy improved by 0.5% and 5.8%， respectively， and mAP@0.5:0.95 improved by 2.8% and 7%， respectively. These improvements satisfied the requirements for deployment on embedded terminals in cars.

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：