检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

936 篇 会议
431 篇 期刊文献
1 册 图书

馆藏范围

1,368 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

981 篇 工学
- 406 篇 控制科学与工程
- 351 篇 软件工程
- 320 篇 计算机科学与技术...
- 276 篇 机械工程
- 137 篇 电气工程
- 124 篇 仪器科学与技术
- 114 篇 电子科学与技术（可...
- 97 篇 信息与通信工程
- 67 篇 航空宇航科学与技...
- 57 篇 交通运输工程
- 46 篇 动力工程及工程热...
- 37 篇 生物工程
- 30 篇 材料科学与工程（可...
- 29 篇 力学（可授工学、理...
- 25 篇 光学工程
- 25 篇 化学工程与技术
- 24 篇 安全科学与工程
- 23 篇 土木工程
- 23 篇 生物医学工程（可授...
- 16 篇 建筑学
440 篇 理学
- 267 篇 数学
- 154 篇 系统科学
- 90 篇 物理学
- 66 篇 统计学（可授理学、...
- 40 篇 生物学
- 23 篇 化学
194 篇 管理学
- 174 篇 管理科学与工程(可...
- 34 篇 工商管理
- 16 篇 图书情报与档案管...
18 篇 军事学
16 篇 经济学
- 16 篇 应用经济学
15 篇 医学
12 篇 法学
9 篇 农学
3 篇 艺术学
1 篇 教育学

主题

33 篇 mathematical mod...
29 篇 feature extracti...
28 篇 optimization
23 篇 uncertainty
21 篇 robustness
20 篇 state estimation
19 篇 legged locomotio...
19 篇 stability analys...
19 篇 trajectory
18 篇 training
17 篇 target tracking
17 篇 accuracy
16 篇 object detection
16 篇 force
16 篇 planning
16 篇 attitude control
16 篇 robot kinematics
15 篇 deep learning
15 篇 three-dimensiona...
15 篇 cameras

机构

282 篇 school of automa...
75 篇 key laboratory o...
56 篇 state key labora...
54 篇 key laboratory o...
52 篇 shaanxi key labo...
46 篇 key laboratory o...
42 篇 school of automa...
38 篇 key laboratory o...
37 篇 shaanxi key labo...
36 篇 state key labora...
35 篇 state key labora...
34 篇 beijing institut...
28 篇 key laboratory o...
26 篇 shaanxi key labo...
25 篇 school of automa...
25 篇 key laboratory o...
24 篇 key laboratory o...
24 篇 national key lab...
23 篇 science and tech...
22 篇 hubei key labora...

作者

92 篇 chen jie
79 篇 jie chen
78 篇 junzheng wang
50 篇 yuanqing xia
47 篇 xiangdong liu
43 篇 jian sun
41 篇 mengyin fu
34 篇 liping yan
33 篇 hongbin ma
30 篇 sun jian
29 篇 ding liu
28 篇 jing li
27 篇 zhen li
26 篇 qiang huang
25 篇 xin bin
25 篇 wang junzheng
25 篇 liu xiangdong
24 篇 chen chen
24 篇 fang hao
23 篇 fu mengyin

语言

1,297 篇 英文
64 篇 中文
8 篇 其他

检索条件"机构=Key Laboratory Intelligent Control and Decision of Complex System"

共 1368 条记录，以下是201-210 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Temperature control system of Thermoelectric Cooler Based on Improved ADRC

Temperature Control System of Thermoelectric Cooler Based on...

引用

第34届中国控制与决策会议

作者： Xiyuan Shan Tao Cai Zhicheng Zong Hongbo Mu School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at the problems containing complex working conditions,modeling difficulties and long-time delay of thermoelectric cooler temperature control system,an improved ADRC control method combining ADRC and Smith predictor is proposed in this *** deals with the disturbances and uncertain dynamics in the system,SP compensates the time delay to improve the control *** with the traditional PID controller,the proposed control method has faster response speed and stronger anti-disturbance ability,meanwhile,overcomes the dependence of Smith predictor on object parameters to a certain *** simulation and experimental verification,a good control effect is obtained,which provides a positive guidance of the related application of thermoelectric cooler.

关键词： Thermoelectric cooler(TEC) Active Disturbance Rejection control(ADRC) Smith Predictor(SP) Temperature control system

来源：评论

学校读者我要写书评

暂无评论

Towards Pose Estimation for Large UAV in Close Range

Towards Pose Estimation for Large UAV in Close Range

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Ni Ou Junzheng Wang Shangfei Liu Jiehao Li State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665465373

This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.

关键词： Point cloud compression Measurement Cloud computing Pose estimation Vision sensors Autonomous aerial vehicles Laser modes

来源：评论

学校读者我要写书评

暂无评论

Power system Events Classification Technology Based on Deep-Learning

Power System Events Classification Technology Based on Deep-...

引用

IEEE International Symposium on Circuits and systems (ISCAS)

作者： Xin Lei Hongwei Ma Bin Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China College of Information Science and Engineering China University of Petroleum (Beijing) Beijing China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

As the complexity of the power system continues to increase, the frequency of the power system anomalies is on the rise. These anomalies have significant and widespread impacts on the stability of the power grid. Therefore, the rapid and accurate classification of these anomalies is crucial in preventing their further propagation and mitigating potential economic losses. This study presents an algorithm based on Phasor Measurement Unit (PMU) data for monitoring the state of power systems and identifying the types of anomalies. First, a dataset for anomaly event classification is created based on PMU data, which is used to train and validate the anomaly event classification model. Subsequently, a robust anomaly event classification model is constructed, consisting of a residual module with one-dimensional Convolutional Neural Networks (CNN) and a cascaded fully connected neural network classifier. This algorithm has undergone rigorous testing in the IEEE New England 39 bus test system, demonstrating exceptional event recognition accuracy.

关键词： Accuracy Power system stability Propagation losses Phasor measurement units Data models Stability analysis Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

An Improved Active Disturbance Rejection control Method for Crane system

An Improved Active Disturbance Rejection Control Method for ...

引用

第34届中国控制与决策会议

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to improve the dynamic performance of the underdriven crane system,an improved linear active disturbance rejection controller(LADRC) based on the new error was *** improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer(LESO).The improved method has two ***,the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances,which will limit the performance of the ***,the pole can be configured by adjusting the coefficient to obtain better dynamic ***,the effectiveness of the proposed method is verified by simulation and *** proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Crane LADRC New Error Underdriven system

来源：评论

学校读者我要写书评

暂无评论

A 3D Point Attacker for LiDAR-Based Localization

A 3D Point Attacker for LiDAR-Based Localization

引用

International Conference on control and Automation (ICCA)

作者： Shiquan Yi Jiakai Gao Yang Lyu Lin Hua Xinkai Liang Quan Pan School of Automation Northwestern Polytechnical University Xi'an Shaanxi PR China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing PR China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

The safety and security issues of autonomous navigation function become the main obstacles that hinder the widespread applications of self-driving cars and unmanned systems. In this paper, we investigate the vulnerability of LiDAR-based localization methods to adversarial attacks. Specifically, we developed a feature-based spoofing attack strategy to degrade the localization performance of LiDAR-based localization algorithms. Reflecting on the vulnerability, we additionally provide a resilient strategy to defend existing LiDAR-based localization methods against this attack. The proposed attack strategy is tested on the KITTI dataset to illustrate its effectiveness.

关键词： Location awareness Simultaneous localization and mapping Laser radar Accuracy Three-dimensional displays Perturbation methods Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Target Recognition Inference Based on Knowledge Graph and Graph Neural Network

Target Recognition Inference Based on Knowledge Graph and Gr...

引用

Chinese Automation Congress (CAC)

作者： Wei Li Hongfeng Xu Yuan Li Beijing Institute of Technology Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In complex environments with vast and diverse information sources, target recognition serves as a crucial precursor to situational analysis, providing the foundation for further decision-making and analysis. Traditional algorithms for target recognition often rely on human experience and rules, necessitating expert knowledge and subjective judgments, which introduces uncertainties. This paper introduces a method for target recognition inference, leveraging Situation Knowledge Graph Convolutional Neural Network (SKGCN). By employing active and passive radar sensor data in complex scenarios, the algorithm processes inputs within a self-constructed situational knowledge graph. It derives vector representations of target entities through aggregation operations among neighboring nodes and extracts perceptual data vectors using the embedding layer. The algorithm calculates the alignment between sensor data and target entities, facilitating target recognition and inference in complex scenarios. Simulation results confirm the effectiveness of the proposed approach.

关键词： Machine learning algorithms Target recognition Soft sensors Weapons Knowledge graphs Feature extraction Inference algorithms Vectors Data mining Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Torque Compensation Model and Touchdown Detection Model of the Hydraulic Quadruped Robot controlled by VMC

Torque Compensation Model and Touchdown Detection Model of t...

引用

第34届中国控制与决策会议

作者： Ranjiang Wang Jiangbo Zhao Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology

In this paper,according to the different dynamic models of the support phase and the swing phase,the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC).This compensation can increase the tracking effect of the foot end on the swing trajectory,reduce the elasticity and damping coefficient of the virtual model method,and increase the flexibility of the *** this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the *** the end of this paper,simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.

关键词： Quadruped robot Torque compensation Touchdown detection Virtual model control

来源：评论

学校读者我要写书评

暂无评论

GAT-Net:A Network using Grid Attention and Transformer for Dynamic Facial Expression Recognition

GAT-Net:A Network using Grid Attention and Transformer for D...

引用

第34届中国控制与决策会议

作者： Wenxin Dai Yaping Dai Kaoru Hirota Shuai Shao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Dynamic facial expression recognition(DFER) in the wild has received widespread attention *** are complex factors such as face occlusion and pose variation in the *** expression recognition has a subtle competition between capturing local features of a human face and obtaining a global feature *** paper proposes an end-to-end DFER network GAT-Net based on the grid attention module and Transformer,which improves the robustness and accuracy of DFER in the ***,GAT-Net is divided into two components:spatial feature extraction and temporal feature *** grid attention module of the spatial feature extraction component guides the network to pay attention to the local salient features of the face,which reduces the interference of field occlusion and non-frontal *** Transformer in the temporal feature processing component guides the network to learn the temporal relationship of high-level semantic features and the global representation of facial expression *** two components balance the subtle competition between local features and global feature representations of facial *** ablation experiment has proved the effectiveness of the grid attention module and *** demonstrate that our GAT-Net outperforms state-of-the-art methods on DFEW and AFEW benchmarks with accuracies of 67.53%,and 50.14% respectively.

关键词： Facial Expression Recognition Deep Learning Attention Mechanism Transformer

来源：评论

学校读者我要写书评

暂无评论

A Robust Multi-AGV Cooperative Path Planning Method Considering Spatiotemporal Distance 5

A Robust Multi-AGV Cooperative Path Planning Method Consider...

引用

5th International Conference on Computer Engineering and intelligent control, ICCEIC 2024

作者： Chen, Maolin Chen, Songhang Lian, Mingchang School of Advanced Manufacturing Fuzhou University Quanzhou China Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou China Fujian College University of Chinese Academy of Sciences Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China

ISBN: (纸本)9798331507992

With the widespread application of Automated Guided Vehicles (AGVs) in warehousing and logistics systems, the optimization of multi-AGV path planning has become a critical issue. Current methods primarily focus on minimizing operating time and energy consumption but often overlook spatiotemporal distances between paths, leading to frequent path conflicts and interferences in the system. This paper proposes a neural network based time window estimation model, designed to generate time windows that better align with dynamic environments. Based on this model, we introduce a collaborative multi-AGV path planning method that optimizes spatiotemporal distances between paths. Compared to the Conflict-Based Search (CBS) method, this approach significantly improves the spatiotemporal distance between AGVs during task execution, enhancing the robustness of AGV clusters while only marginally increasing time costs. © 2024 IEEE.

关键词： Automatic guided vehicles

来源：评论

学校读者我要写书评

暂无评论

Data-Driven control for Nonlinear Multi-Agent systems Using Reinforcement Learning

Data-Driven Control for Nonlinear Multi-Agent Systems Using ...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Renzhi Liu Hongru Ren Hui Ma Hongyi Li Renquan Lu School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control and Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou China School of Mathematics and Statistics Guangdong University of Technology Guangzhou China School of Electronic and Information Engineering and Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest University Chongqing China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

In this paper, a new reinforcement learning-based model-free adaptive control algorithm is introduced for discrete-time nonlinear multi-agent systems with unknown dynamics, while the equivalent dynamic linearization algorithm is applied to design the optimal controller. The strategy for Q-Learning and the actor-critic neural network are specifically redesigned to achieve consensus control in multi-agent systems. The proposed reinforcement learning algorithm can adjust the dynamic linearization parameters in real-time only based on input and output data. The stability of the closed-loop system is proven by Lyapunov theorem. Furthermore, the method’s effectiveness is verified by a numerical simulation.

关键词： Adaptation models Target tracking Q-learning Heuristic algorithms Numerical simulation Stability analysis Real-time systems

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共137页 << < 17 18 19 20 21 22 23 24 25 26 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：