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

716 篇 会议

馆藏范围

716 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

324 篇 工学
- 186 篇 计算机科学与技术...
- 180 篇 控制科学与工程
- 168 篇 软件工程
- 46 篇 机械工程
- 41 篇 电气工程
- 29 篇 信息与通信工程
- 26 篇 交通运输工程
- 21 篇 生物医学工程（可授...
- 16 篇 电子科学与技术（可...
- 16 篇 航空宇航科学与技...
- 14 篇 光学工程
- 13 篇 石油与天然气工程
- 11 篇 安全科学与工程
- 10 篇 动力工程及工程热...
- 10 篇 土木工程
- 10 篇 船舶与海洋工程
- 10 篇 生物工程
- 9 篇 仪器科学与技术
- 9 篇 建筑学
- 9 篇 化学工程与技术
148 篇 理学
- 83 篇 数学
- 57 篇 系统科学
- 20 篇 统计学（可授理学、...
- 17 篇 物理学
- 11 篇 生物学
28 篇 管理学
- 22 篇 管理科学与工程(可...
- 10 篇 图书情报与档案管...
- 9 篇 工商管理
9 篇 医学
- 9 篇 基础医学(可授医学...
- 9 篇 临床医学
4 篇 经济学
4 篇 教育学
4 篇 农学
3 篇 法学
2 篇 军事学
1 篇 文学

主题

179 篇 learning systems
83 篇 control systems
67 篇 accuracy
59 篇 simulation
53 篇 adaptation model...
50 篇 predictive model...
48 篇 data models
40 篇 training
36 篇 process control
34 篇 stability analys...
34 篇 heuristic algori...
32 篇 uncertainty
29 篇 neural networks
29 篇 numerical simula...
29 篇 feature extracti...
28 篇 observers
26 篇 adaptive systems
25 篇 reinforcement le...
24 篇 noise
22 篇 deep learning

机构

24 篇 school of electr...
14 篇 school of mathem...
12 篇 school of electr...
12 篇 school of automa...
11 篇 faculty of infor...
9 篇 college of contr...
9 篇 kunming universi...
9 篇 college of contr...
8 篇 college of artif...
8 篇 school of artifi...
8 篇 college of artif...
8 篇 faculty of mecha...
8 篇 beijing key labo...
8 篇 yunnan key labor...
8 篇 school of electr...
7 篇 school of automa...
7 篇 college of infor...
7 篇 state key labora...
6 篇 school of electr...
6 篇 school of automa...

作者

18 篇 wang li
18 篇 li wang
11 篇 deqing huang
11 篇 ji honghai
11 篇 liu shida
11 篇 shida liu
11 篇 honghai ji
10 篇 huang deqing
8 篇 darong huang
7 篇 xiaoli li
6 篇 kang wang
6 篇 feng li
6 篇 song zhihuan
6 篇 ruikun zhang
6 篇 zhou zhou
5 篇 ye ren
5 篇 fan lingling
5 篇 liu yang
5 篇 ren ye
5 篇 zengqiang chen

语言

632 篇 英文
84 篇 其他

检索条件"任意字段=13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024"

共 716 条记录，以下是451-460 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：

A Velocity Tracking Method for Quadruped Robot with Rhythm controller

A Velocity Tracking Method for Quadruped Robot with Rhythm C...

引用

data driven control and learning systems (ddcls)

作者： Xiaoping Zhang Yitong Wu Zhongchen Xiu School of Electrical and Control Engineering North China University of Technology Beijing China Department of Engineering University of Cambridge Cambridge UK

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In the motion performance of quadruped robots, the velocity is a very important item. It is hoped that a quadruped robot can move stably in accordance with the expected velocity. In this work, a velocity autonomous tracking method is proposed to realize real-time velocity tracking during the movement of quadruped robots. Firstly, the gait learning process of a quadruped robot is completed based on deep reinforcement learning, and the velocity adaptation ranges of different gaits are obtained. After that, the gait selection and velocity tracking controller selects the gait according to the desired velocity firstly, and makes periodic dynamic adjustment according to the velocity error signal after, thus completing the velocity tacking of the robot. the effectiveness of the method is verified by simulation experiments. the quadruped robot can well complete the velocity tracking task under different gaits, and the movement is relatively stable.

关键词： Legged locomotion learning systems Tracking Heuristic algorithms Rhythm Deep reinforcement learning control systems

来源：评论

学校读者我要写书评

暂无评论

Stock Price Prediction Based on Relative Strength Index, Moving Average Convergence Divergence and XGBoost Model

Stock Price Prediction Based on Relative Strength Index, Mov...

引用

data driven control and learning systems (ddcls)

作者： Lai Ming Guici Chen College of Science Wuhan University of Science and Technology Wuhan Hubei Province Key Laboratory of System Science in Metallurgical Process Wuhan University of Science and Technology Wuhan

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Stock price prediction is crucial in shaping investment strategies, facilitating risk management, and aiding decision-making processes for both investors and financial institutions. Based on the trading data of ZTE's stock from 2015 to 2022, this paper utilizes XGBoost model to forecast the stock price and compares it with the actual value. the research includes calculation of exponential moving average and simple moving average, analysis of relative strength index, calculation of moving average convergence divergence, and application of XGBoost regression model for stock price prediction. By comparing the predicted value with the actual value, the prediction ability of XGBoost model is verified. the results of this study provide a feasible stock price prediction method for investors and financial institutions, and have important reference value for formulating investment strategies and managing risks.

关键词： learning systems Machine learning algorithms Stability criteria Predictive models Market research data models Indexes

来源：评论

学校读者我要写书评

暂无评论

Identification Algorithm for Wiener Nonlinear systems Based on Adaptive Neural Fuzzy Networks

Identification Algorithm for Wiener Nonlinear Systems Based ...

引用

data driven control and learning systems (ddcls)

作者： Zhou Zhou Yuesong Yang Feng Li Yanzong Zhu School of Electrical and Information Engineering Jiangsu University of Technology Changzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper discusses identification method of a class of Wiener nonlinear systems based on adaptive neural fuzzy networks. the Wiener system in current research is comprised of a dynamic linear block modelled by transfer function and a static nonlinear block approximated by a five-layer adaptive neural fuzzy networks. the special test signals involving separable signals and random signals are designed to achieve separation identification of the Wiener system. Firstly, we estimate the unknown parameters of the transfer function by applying the correlation analysis technique depending on separable signals input-output measurements. Secondly, employing the cluster method and the recursive least squares algorithm to estimate the adaptive neural fuzzy networks. the simulation results demonstrate that the developed identification approach can identify with effect the Wiener systems based on adaptive neural fuzzy networks and the adaptive neural fuzzy networks can well model the nonlinearity of the Wiener system.

关键词： learning systems Adaptation models Adaptive systems Correlation Simulation Neural networks Transfer functions

来源：评论

学校读者我要写书评

暂无评论

A Novel Model-Free Adaptive Recursive Optimal control for Time-Varying Nonlinear systems

A Novel Model-Free Adaptive Recursive Optimal Control for Ti...

引用

data driven control and learning systems (ddcls)

作者： Honghai Ji Yue You Shida Liu Li Wang Wei Wang School of Electronics & Control Engineering North China University of Technology Beijing China Powerchina South Construction Investment Co. Ltd Shenzhen China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, A novel model-free adaptive recursive optimal control (MFAROC) is proposed for time-varying nonlinear systems. On the basis of the optimization index designed based on the recursive idea, a novel time-varying parameter called information weight (IW) is derived and proved to be derived, which effectively solves the problem of difficult establishment of the controlled model. Meanwhile, the control law is designed by using the symmetry principle, and the model-free adaptive recursive optimization control algorithm (MFAROC) is investigated, which effectively compensates for the time-varying nature of the system and solves the time-varying problem of the parameters, structure, and order of the nonlinear system. the algorithm is an important data-driven control method involving adaptive learning capability of nonlinear systems. the effectiveness of the MFAROC algorithm is verified by numerical simulation and simulation of the speed tracking control example of the transportation system. Compared with the existing MFAC and incremental PID, our MFAROC proves that the convergence speed is significantly improved and the tracking error is significantly reduced by some comparative analyses.

关键词： Adaptation models PI control Optimal control Transportation Numerical simulation PD control Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

First Order Nonlinear Filtering Adaptive Dynamic Surface Fixed Time Fault-Tolerant control Method for Nonlinear Pure Feedback systems

First Order Nonlinear Filtering Adaptive Dynamic Surface Fix...

引用

data driven control and learning systems (ddcls)

作者： Leijiao Ge Xingyun Li School of Electrical and Information Engineering Tianjin University Tianjin School of Mechanical Engineering Tianjin University of Science and Technology Tianjin

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

For a class of uncertain functions and nonlinear pure feedback systems with actuator faults, an adaptive dynamic surface fixed time fault-tolerant control method based on a first-order nonlinear filter is proposed. Using Lagrange's mean value theorem, the non-affine function in the system is treated and the control input signal is decoupled effectively. the dynamic surface is designed to reduce the input parameters of radial basis function neural network. the fuzzy logic control technique is used to approach the unknown function. the fixed-time control theory is used to ensure that the output signal can track the expected output signal in a fixed time. through theoretical analysis, it is proved that the tracking error of the system converges in a small neighborhood of the origin, and the convergence time is independent of the initial state of the system. Finally, through a simulation example, the proposed method improves the error accuracy by about 25% compared with the comparison method.

关键词： learning systems Fuzzy logic Fault tolerance Adaptive systems Fault tolerant systems Radial basis function networks Nonlinear filters

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Dynamic System Based on SAE-LDS Model for Fault Diagnosis

Nonlinear Dynamic System Based on SAE-LDS Model for Fault Di...

引用

data driven control and learning systems (ddcls)

作者： Xiaochu Tang Yi Zhang Xinmin Zhang Zhihuan Song School of Automation Shenyang Aerospace University Shenyang Liaoning Province China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou Zhejiang Province China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Dynamic, uncertainty and nonlinearity are three very important characteristics of complex industrial process data. In this paper, a method of fault detection and classification based on stacked autoencoder-linear dynamic system (SAE-LDS) model is proposed. this method aims to simultaneously consider multiple characteristics of industrial process data for fault detection and classification. Firstly, the deep learning algorithm SAE is used to mine the nonlinear characteristic of process data. On this basis, the SAE model is embedded into the LDS model. the LDS model is used to further extract the dynamics and uncertainty, so as to establish a SAE-LDS model that can comprehensively consider multiple characteristics of data. Finally, the SAE-LDS model is applied to the TE process, compared with the traditional method for fault detection and fault classification. the experimental results show that SAE- LDS model has good effectiveness.

关键词： Fault diagnosis learning systems Uncertainty Accuracy Fault detection Simulation Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Fault Estimation for Nonlinear systems with Disturbance Based on Reinforcement Iterative learning Strategy

Fault Estimation for Nonlinear Systems with Disturbance Base...

引用

data driven control and learning systems (ddcls)

作者： Zhengquan Chen Ruirui Huang Zhiheng Zhang Yandong Hou School of Computer and Information Engineering Henan University Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Artificial Intelligence Henan University Zhengzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper addresses the problem of low fault estimation accuracy in Lipschitz nonlinear systems with external disturbances, presenting an innovative strategy based on a Reinforcement Iterative learning (RIL) framework. Initially, we conducted precise mathematical modeling, comprehensively considering the impact of Lipschitz non-linearity and external disturbances. Subsequently, an iterative learning fault observer was designed, and the optimization problem for its parameters was reformulated into a reinforcement learning task, clearly defining the states, actions, and reward functions. Employing the Advantage Actor-Critic (A2C) reinforcement learning method, we optimized the gain parameters of the iterative learning fault estimator to approximate non-linearity. Simultaneously, with the increase in iteration count, the neural network weights were continually optimized, achieving accurate fault estimation. Experimental results demonstrate a significant improvement in fault estimation using the proposed method.

关键词： Sufficient conditions Accuracy Neural networks Estimation Reinforcement learning Observers Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Soft Sensor Development Based on Large-Scale Pseudo Labeling Optimization

Soft Sensor Development Based on Large-Scale Pseudo Labeling...

引用

data driven control and learning systems (ddcls)

作者： Guangkun Liu Huaiping Jin Bin Wang Biao Yang Bin Qian Department of Automation Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

data-driven soft sensor techniques enable online prediction of key quality variables. However, in real industry, the expensive cost of manual labeling leads to the abundance of unlabeled data and the scarcity of labeled data, which becomes a major obstacle to establishing high-precision data-driven soft sensing. To address this problem, a method based on large-scale pseudo-labeling optimization, LSPLO, is proposed. this method, by introducing confidence assessment, fixes the pseudo labels assessed as high-confidence during optimization, while the low-confidence pseudo labels are used as new decision variables after dimensionality reduction to continue optimization. the original decision variables are reinitialized using superior pseudo labels, and stepwise dimensionality reduction and optimization are performed to obtain the optimal pseudo labels. the superiority of the proposed method LSPLO is demonstrated by a real industrial case of the Chlortetracycline (CTC) fermentation process.

关键词： Dimensionality reduction Industries Soft sensors Estimation Process control Transforms Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Switching System-Based Event-Triggered Sampled-data control for Multi-Area Power systems Under DoS Attacks: A data-driven Method

Switching System-Based Event-Triggered Sampled-Data Control ...

引用

data driven control and learning systems (ddcls)

作者： Rui Hou Li Jia Jianfang Li Bo Zhu School of Mechatronic Engineering and Automation Shanghai University Shanghai P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

the reliance of modern power systems on open communication networks for load frequency control (LFC) increases vulnerability to cyber-attacks, particularly denial-of-service (DoS) attacks. this study explores a novel switching system-based resilient event-triggered sampled-data control for LFC using a data-driven method. Firstly, a linear data-dependent model for power systems is presented addressing unknown nonlinearities, treating sampling period as a vital design parameter. Further, the LFC system is modeled as multiple switching subsystems under DoS attacks, and then a new adaptive sampled-data controller is proposed to accomplish frequency regulation while withstanding the attacks. Additionally, an event-triggered scheduling mechanism (ETSM) is considered to optimize bandwidth resources for data transmission during sampling. To assess the proposed LFC scheme, a new stability criterion and analysis method, employing the average dwell time (ADT) technique and Lyapunov stability theory, is introduced. Finally, the scheme's effectiveness is demonstrated through evaluation on a three-area power system.

关键词： Adaptation models System dynamics Stability criteria Switches Power system stability control systems Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Model-free adaptive predictive control of nonlinear sandwich systems with input constraints

Model-free adaptive predictive control of nonlinear sandwich...

引用

data driven control and learning systems (ddcls)

作者： Jianguo Dong Jun Liu Xiaoqing Jiang Ziyu Wang Huarui Luo Zhao Shi School of Automation Southeast University Nanjing China School of Information and Control Engineering China University of Mining and Technology Xuzhou China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Since nonlinear sandwich systems with input constraints are difficult to establish their model accurately, a model-free adaptive predictive control (MFAPC) based on compact format dynamic linearization is proposed. the criterion function of MFAPC algorithm is applied to build a quadratic programming problem with input constraints. the optimal control input signal can be obtained by solving the quadratic programming problem. In order to eliminate the adverse effect of random measurement noise on solving the optimal input signal and the stability of tracking control results, the tracking differentiator is used to estimate the output measurement signal. the stability of the control algorithm is also analyzed and proved. Finally, the merit of the proposed control algorithm is verified by example test.

关键词： Adaptation models Adaptive systems Heuristic algorithms Stability criteria Predictive models Prediction algorithms Quadratic programming

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72页 << < 42 43 44 45 46 47 48 49 50 51 > >>

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：