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

2,733 篇 会议
1,580 篇 期刊文献
28 册 图书

馆藏范围

4,341 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,154 篇 工学
- 1,051 篇 控制科学与工程
- 725 篇 计算机科学与技术...
- 642 篇 软件工程
- 422 篇 电气工程
- 347 篇 机械工程
- 246 篇 电子科学与技术（可...
- 188 篇 信息与通信工程
- 141 篇 动力工程及工程热...
- 126 篇 生物医学工程（可授...
- 122 篇 仪器科学与技术
- 115 篇 化学工程与技术
- 113 篇 力学（可授工学、理...
- 113 篇 生物工程
- 97 篇 土木工程
- 84 篇 材料科学与工程（可...
- 83 篇 航空宇航科学与技...
- 78 篇 交通运输工程
- 66 篇 建筑学
1,425 篇 理学
- 820 篇 数学
- 529 篇 系统科学
- 273 篇 物理学
- 197 篇 统计学（可授理学、...
- 145 篇 生物学
- 108 篇 化学
303 篇 管理学
- 237 篇 管理科学与工程(可...
- 103 篇 工商管理
- 69 篇 图书情报与档案管...
117 篇 医学
- 97 篇 临床医学
- 70 篇 基础医学(可授医学...
- 50 篇 药学(可授医学、理...
47 篇 经济学
44 篇 法学
20 篇 教育学
17 篇 农学
6 篇 军事学
5 篇 文学

主题

253 篇 control systems
174 篇 automatic contro...
132 篇 mathematical mod...
128 篇 optimization
120 篇 genetic algorith...
118 篇 systems engineer...
105 篇 neural networks
93 篇 nonlinear system...
93 篇 optimal control
92 篇 robustness
88 篇 predictive contr...
86 篇 fault detection
84 篇 robust control
84 篇 process control
83 篇 adaptive control
79 篇 linear systems
78 篇 predictive model...
74 篇 convergence
72 篇 fuzzy logic
70 篇 computational mo...

机构

243 篇 department of au...
126 篇 department of au...
121 篇 department of au...
106 篇 department of au...
105 篇 department of au...
97 篇 department of au...
43 篇 department of au...
38 篇 department of au...
35 篇 institute for sy...
34 篇 department of au...
33 篇 department of au...
26 篇 department of au...
25 篇 school of electr...
25 篇 automatic contro...
24 篇 department of au...
23 篇 department of au...
23 篇 department of au...
22 篇 beijing key labo...
21 篇 institute for sy...
19 篇 department of au...

作者

85 篇 d.a. linkens
71 篇 tokhi m.o.
64 篇 p.j. fleming
57 篇 d.h. owens
50 篇 m. mahfouf
49 篇 m.o. tokhi
47 篇 necoara ion
46 篇 j.a. rossiter
44 篇 mahdi mahfouf
40 篇 e. rogers
38 篇 rossiter j.a.
37 篇 m. o. tokhi
35 篇 mahfouf m.
35 篇 ion necoara
34 篇 lyudmila mihaylo...
32 篇 allgöwer frank
31 篇 frank allgöwer
31 篇 linkens d.a.
30 篇 v. kadirkamanath...
29 篇 owens d.h.

语言

4,227 篇 英文
87 篇 其他
24 篇 中文
2 篇 日文

检索条件"机构=Department of Systems Engineering and Automatic Control Polytechnic"

共 4341 条记录，以下是51-60 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：

Output Tracking for Uncertain Time-Delay systems via Robust Reinforcement Learning control

Output Tracking for Uncertain Time-Delay Systems via Robust ...

引用

第43届中国控制会议

作者： Zezhi Tang J Anthony Rossiter Xin Jin Benyuan Zhang George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The composite optimal output tracking control problem of time-delay uncertain systems is investigated in this paper. To improve the robustness of the uncertain systems, a disturbance observer-based(DOB) compensation scheme is proposed to reduce the influence of the *** further enhance the control efficiency, we incorporate a Smith predictor into the control framework to precisely predict future states of the delayed system. Subsequently, a composite actor-critic reinforcement learning(RL) scheme is built for approximating both the ideal value function associated with the compensated system and the optimal control policy in real-time, by augmenting the system states with the output tracking error. To counteract the impact of the probing signal, concurrent learning is employed in this paper with the data collected from the known system *** results based on an experimental platform of slot die coating machines demonstrate the effectiveness of the proposed scheme.

关键词： Smith Output Tracking for Uncertain Time-Delay systems via Robust Reinforcement Learning control

来源：评论

学校读者我要写书评

暂无评论

Tide Level Prediction Using NARX-based Recurrent Neural Networks 27

Tide Level Prediction Using NARX-based Recurrent Neural Netw...

引用

27th International Conference on Automation and Computing, ICAC 2022

作者： Nikentari, Nerfita Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Tide level forecasting is one of major components in oceanography and marine research. The future prediction of tides is an important issue for human and environment. This study proposes new tide level prediction methods with multiple input multiple output (MIMO) approach based on nonlinear autoregressive with exogenous inputs (NARX) model and three types of recurrent neural networks (RNNs), namely, long short-term memory (LSTM), bi-directional long short-term memory (biLSTM) and gated recurrent unit (GRU) networks. We develop three types of NARX models: NARX-LSTM, NARX-biLSTM and NARX-GRU. We evaluate the three models and compare their performances with LSTM, biLSTM and GRU network models. It turns out that the proposed MIMO NARX based RNN models, especially NARX-LSTM and NARX-GRU have better performance in comparison with their RNN counterparts (i.e., LSTM, biLSTM, and GRU). The NARX-GRU model shows the best performance for one step and three step ahead prediction in terms of RMSE in each location and average RMSE, while NARX-LSTM performs better for two steps ahead prediction in terms average RMSE. The results also show that the mixture of RNN and NARX improves the performance of RNN model for all the four tasks at four locations in the UK (Wick, Workington, Ullapol and New Heaven) and for the three time horizons (i.e., 1, 2 and 3 steps ahead). © 2022 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

A Hybrid 1DCNN-SVM Model for Bearing Fault Recognition and Classification 27

A Hybrid 1DCNN-SVM Model for Bearing Fault Recognition and C...

引用

27th International Conference on Automation and Computing, ICAC 2022

作者： Wang, Guoliang Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Rolling bearings play a significant role in the operation of rotating machinery. Finding bearing faults in the early stage can not only keep machinery running safely but also avoid economic loss. Traditional machine learning (ML) and deep learning (DL) are two important classes of fault diagnosis methods. The process of feature extraction is significant for ML based methods and many signal processing techniques have been used in this process. However, when dealing with massive and complex signals, features extracted by these techniques may not fully describe the characteristics of faults. Convolutional neural network (CNN) models are applied in many areas, including image identification and classification, pattern recognition, and speech processing. In this paper, a novel hybrid model by combining one dimensional CNN (1DCNN) and support vector machine (SVM) is proposed for bearing fault diagnosis and classification, which is called 1DCNN-SVM model or method. The first part of the model, 1DCNN, is used to extract features of raw data, whereas the second part, SVM, is employed to carry out the fault recognition and classification tasks. The evaluation of the proposed method is operated based on a real dataset. The experiment results show that the fault diagnosis accuracy of proposed method based on the hybrid model is highly improved compared to the traditional SVM based methods. © 2022 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Efficient Mask Attention-Based NARMAX (MAB-NARMAX) Model Identification 27

Efficient Mask Attention-Based NARMAX (MAB-NARMAX) Model Ide...

引用

27th International Conference on Automation and Computing, ICAC 2022

作者： Sun, Yiming Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Model structure selection is crucial in system identification and data-driven modelling. Many spurious candidate variables can influence the determination of model structures due to the lack of prior knowledge of the system of interest. The commonly used method is to test as many possible models as possible and select a set of best models. This study proposes a novel mask attention-based NARMRAX (MAB-NARMAX) modelling method for nonlinear dynamic system identification. The mask attention mechanism comes from the widely used neural network Transformer to reduce the dependency of the features and neurons. The performance of the proposed method is tested on three simulation datasets. Results show that the proposed MAB-NARMAX modelling framework has convincing multistep-ahead prediction performance for nonlinear system identification in that it can produce the precious model structure. Even when the data are polluted with high noise (resulting in low SNR), the proposed method can still generate reliable system models compared with the state-of-the-art machine learning methods, e.g., LASSO and LSTM. © 2022 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Analysing and Modelling Human Trust to a Navigation Robot 2

Analysing and Modelling Human Trust to a Navigation Robot

引用

2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Onyeoru, Happy Chidi Wirth, Christopher Giles, Joshua Arvaneh, Mahnaz University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom School of Medical Sciences University of Manchester United Kingdom

ISBN: (纸本)9798350300802

Human trust plays a crucial role in Human-Machine Interactions (HMIs) within autonomous systems. This paper delves into the factors that influence human trust in machines, including varying error rates and types made by the machine, as well as the human's ability to intervene and rectify errors. To explore these factors, we conducted three scenarios involving a simulated claw robot navigating through multiple objects to detect and locate a target object. The first scenario examined the effect of changing error rates on human trust in the machine. In the second scenario, we investigated how variability in speed and accuracy of reaching the target impacted human trust. Lastly, we explored whether human trust in the machine changed when individuals had the capability to intervene and correct severe errors made by the machine. We then proposed a regression model to estimate human trust. Our results showed that human trust is significantly affected by changes in error rates. Our participants reported a higher trust on robot with low speed but higher accuracy in performing the task than the robot with high speed but lower accuracy. Interestingly, the ability to intervene and correct the robot's errors improved the participants' trust in the robot. Our regression result showed that we can estimate trust using different type of errors committed by machine which can be applied in real world scenarios. © 2023 IEEE.

关键词： computational modelling error rates human-machine interactions (HMIs) machine or robot action perceptions target identification trust

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Medical and Healthcare Data Analysis and Modelling: Case Studies and Performance Comparisons of Different Methods 27

Machine Learning for Medical and Healthcare Data Analysis an...

引用

27th International Conference on Automation and Computing, ICAC 2022

作者： Sun, Bo Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

In smart healthcare, binary classification is one of the most important tasks for disease or clinical outcome prediction. Machine learning (ML) methods have great potential to discover knowledge from data. While there are a wide range of ML methods that are potentially useful, the selection, design and implementation of an appropriate method from a variety of ML models for specific prediction tasks is still quite challenging in many medical and healthcare data modelling tasks. This paper investigates, evaluate and compares nine typical representative ML methods using four clinical and healthcare datasets. The main attention is paid to the strengths and weaknesses of these methods and provide suggestions to researchers in related fields. Results demonstrate that ensemble learning (such as Adaboost and random forest) outperform the other approaches in prediction accuracy and interpretability. © 2022 IEEE.

关键词： Adaptive boosting

来源：评论

学校读者我要写书评

暂无评论

Safe Motion Along Harmonic Potential Surfaces with Cardinal Spline Dirichlet Boundary Conditions 63

Safe Motion Along Harmonic Potential Surfaces with Cardinal ...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Nicu, Theodor-Gabriel Stoican, Florin Ioan, Daniel Prodan, Ionela Department of Automatic Control and Systems Engineering Romania 313 Splaiul Independenţei Sector 6 Bucharest060042 Romania Lcis ValenceF-26000 France

ISBN: (纸本)9798350316339

This work pertains to the generation and use of harmonic functions for obstacle avoidance and target tracking. For each cell of a polyhedral complex, we generate a harmonic potential surface from a Dirichlet-type condition on its boundary. The condition is expressed as a smooth cardinal B-spline curve, thus allowing an efficient computation of the potential which avoids the large gradients characteristic to the piecewise constant boundary conditions usually employed in the literature. Enumerating all pairs of 'in' and 'out' facets for each feasible cell (one not part of the obstacles) and attaching a relevant cost to each such pair (e.g., proportional to the path length inside the cell), we arrive at a directed graph where, by construction, all possible paths linking the source and the target avoid the obstacles. The optimal path results from a variation of Dijkstra's algorithm. © 2024 IEEE.

关键词： Harmonic analysis

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning Method for control of Mixed Autonomy Traffic systems

Deep Reinforcement Learning Method for Control of Mixed Auto...

引用

2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent systems, MFI 2024

作者： Liu, Xingyu Apriaskar, Esa Mihaylova, Lyudmila University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Universitas Negeri Semarang Faculty of Engineering Department of Electrical Engineering Semarang50229 Indonesia

ISBN: (纸本)9798350368031

The introduction of autonomous vehicles (AVs) presents a novel approach to regulating and optimising traffic flow through the automated control of AVs. In this context, the AV is defined as the actuator and an optimal control policy is desired to make control decisions. Deep Reinforcement Learning (DRL) is a novel method which aims to maximize the cumulative rewards given by the predefined reward function by making sequential decisions in a stochastic environment. In light of the above, we propose a DRL-based vehicular control method to train an optimal policy for the control of AV in a model-free fashion, and consequently improve the traffic efficiency with the obtained control policy. A single-lane circular road environment with both AV and human-driven vehicles is selected to serve as the mixed autonomy traffic system in the Simulation of Urban MObility (SUMO) [1] traffic simulator, and the Proximal Policy Optimization (PPO) algorithm is applied for the policy improvement. Simulation results demonstrate that our strategy is effective in mitigating the unstable stop-and-go waves, increasing 67.7% of the average driving speed and reducing 19.3% of the average energy consumption in a closed-ring road environment. © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Robust Sliding Mode control of a Quadrotor With Disturbance Rejection for Enhanced Stability and Performance 6

Robust Sliding Mode Control of a Quadrotor With Disturbance ...

引用

6th International Conference on Robotics and Automation in Industry, ICRAI 2024

作者： Ullah, Hameed Zarin, Owais Ahmad, Irfan Ahmad, Sarfraz Abbas, Ansar Lippiello, Vincenzo University of Naples Federico II Department of Electrical Engineering and Information Technology Naples Italy Riphah International University Department of Electrical Engineering Islamabad Pakistan School of Bilbao - EIB/BIE University of the Basque Country - UPV/EHU Automatic Control Group ACG Department of Automatic Control and Systems Engineering Rafael Moreno 3 Bilbao48013 Spain CEME Department of Electrical Engineering Islamabad Pakistan

ISBN: (纸本)9798350355703

This research presents a comprehensive analysis of quadrotor stabilization and trajectory tracking control using Proportional-Integral-Derivative (PID) and Sliding Mode control (SMC) with integrated disturbance rejection. The nonlinear dynamics of the quadrotor are formulated using the Newton-Euler approach, accounting for six degrees of freedom. The PID controller is implemented as a baseline, while the SMC is designed for enhanced robustness to model uncertainties and external perturbations, with a disturbance observer for managing time-varying disturbances. A rigorous Lyapunov stability proof ensures global asymptotic stability of the SMC-controlled system. Extensive simulations evaluate both controllers in terms of tracking accuracy, control effort, and robustness to external disturbances. Results show that SMC outperforms PID in dis-turbance rejection, tracking accuracy, and robustness, making it ideal for UAV applications in complex environments. © 2024 IEEE.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Optimal Energy Exchange of Two Electric Vehicle Charging Stations with Solar-Hydrogen-Battery Storage systems 58

Optimal Energy Exchange of Two Electric Vehicle Charging Sta...

引用

58th International Universities Power engineering Conference, UPEC 2023

作者： Duan, Lijia Lai, Chun Sing Taylor, Gareth Zhang, Xin Brunel University Department of Electronic and Electrical Enginnering London United Kingdom University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom

ISBN: (纸本)9798350316834

This paper presents an optimisation method for the direct energy exchange between two electric vehicle (EV) charging stations located in the UK. Each EV charging station consists of solar panels, hydrogen and battery energy storage systems (SHBS). The stations are interconnected through a energy exchange system that enables the transfer of excess energy from one station to the other. The objective function of SHBS charging stations is to minimize the capital and operation and maintenance costs of the stations. The system constraints are the power output of individual components, as well as the power balance between SHBS charging stations and EV charging demand. Genetic Algorithm is used to optimize the system, considering various factors such as the size of the solar panels and hydrogen storage tanks, the capacity of the electric vehicle chargers, and the amount of energy exchanged between the two stations. The optimized system yields substantial cost savings. © 2023 IEEE.

关键词： Genetic algorithms

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435页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：