检索结果-内蒙古大学图书馆

Designing Discrete Predictor-Based Controllers for Networked Control Systems with Time-varying Delays:Application to A Visual Servo Inverted Pendulum System

引用

IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1763-1777页

作者： Yang Deng Vincent Léchappé Changda Zhang Emmanuel Moulay Dajun Du Franck Plestan Qing-Long Han the Department of Automation Tsinghua UniversityBeijing 100084China the Université de Lyon INSA de LyonECLUniversitéClaude Bernard Lyon 1CNRSAmpèreF-69621VilleurbanneFranc the Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 20072China the XLIM(UMR CNRS 7252) Université de Poitiers11 bd Marie et Pierre Curie86073 Poitiers Cedex 9France IEEE the Nantes Université école Centrale NantesCNRSLS2NUMR 6004F-44000 NantesFrance the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVictoria 3122Australia

A discrete predictor-based control method is developed for a class of linear time-invariant networked control systems with a sensor-to-controller time-varying delay and a controller-to-actuator uncertain constant delay,which can be potentially applied to vision-based control *** control scheme is composed of a state prediction and a discrete predictor-based *** state prediction is used to compensate for the effect of the sensor-to-controller delay,and the system can be stabilized by the discrete predictor-based ***,it is shown that the control scheme is also robust with respect to slight message ***,the main theoretical results are illustrated by simulation results and experimental results based on a networked visual servo inverted pendulum system.

关键词： Discrete predictor-based control inverted pendulum system networked control system time-varying delay vision-based control

来源：评论

学校读者我要写书评

暂无评论

Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

引用

CAAI Transactions on Intelligence Technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

来源：评论

学校读者我要写书评

暂无评论

Simplified Control Strategies for Power Converters in a Grid-Connected Hybrid DC-AC Microgrid

Simplified Control Strategies for Power Converters in a Grid...

引用

Future Energy Solutions (FES), International Conference on

作者： Tiago Davi Curi Busarello Marcelo Godoy Simões Hannu Laaksonen Kimmo Kauhaniemi Department of Control Automation and Computing Engineering Federal University of Santa Catarina Blumenau Brazil School of Technology and Innovations University of Vaasa Vaasa Finland

Many typical converter control strategies used in microgrids are complex or require modifications in the power structure. The complexities are due coupling effects among controllers and time-delay caused in exchanging information in the system. This paper proposes simplified control strategies for power converters in a grid-connected hybrid DC-AC microgrid, aiming to ensure precise voltage and current regulation. The used controllers are proportional-resonant, integral-double-lead, proportional-integral and single integral controller. In this paper, the methodology for tuning each controller is carefully described in detail and recommendation for choosing their bandwidth is given. Then, the designed controllers are discretized through the Backward-Euler approximation. The power converters of the microgrid are an inverter, a Buck, a Boost and a bidirectional DC-DC. A case study is conducted through simulations with Matlab/Simulink. Results show that the controlled variables follow their reference signals with negligible steady-state error, proving the efficacy of the simplified control strategies and allowing an stable operation of the microgrid.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An integrated monitoring system based on deep learning tools for industrial process ⁎

引用

IFAC-PapersOnLine 2024年第4期58卷 168-173页

作者： Adrián Rodríguez-Ramos Cristina Verde Orestes Llanes-Santiago Department of Automation and Computing Universidad Tecnológica de la Habana José Antonio Echeverría Cujae La Habana Cuba Engineering Institute Universidad Nacional Autónoma de México (UNAM) Distrito Federal Mexico

The Industry 4.0 initiative aims to obtain high levels of productivity and efficiency more competitive final products, and compliance with demanding regulations related to industrial safety and cybersecurity. To achieve these goals, industrial systems must be equipped with condition monitoring systems for the early detection and localization of cyberattacks and faults. This paper proposes a robust condition-monitoring strategy to detect and locate faults and cyberattacks in an integrate way using Deep Learning algorithms. The proposal was validated using a Tennessee Eastman (TE) process with excellent results. The proposed strategy was compared with other condition monitoring schemes showing a better performance.

关键词： Industry 4.0 Cybersecurity Fault diagnosis Deep learning

来源：评论

学校读者我要写书评

暂无评论

A multi-view comparative learning method for spatial transcriptomics data clustering

A multi-view comparative learning method for spatial transcr...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Peng, Wei Zhang, Zhihao Dai, Wei Fu, Xiaodong Liu, Li Liu, Lijun Yu, Ning Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China Kunming University of Science and Technology Computer Technology Application Key Lab of Yunnan Province Kunming China State University of New York The College at Brockport Department of Computing Sciences BrockportNY14422 United States

ISBN: (纸本)9798350337488

Clustering individual cells or spots based on their gene expression profiles in a spatial context is a powerful approach to uncovering the underlying biological diversity and relationships among cells. The intricate information within spatial transcriptomics data demands sophisticated algorithms that effectively integrate gene expression, cell position, and tissue image data for accurate cell or spot clustering. This work proposes a Multi-View Comparative Learning method for clustering Spatial Transcriptomics data (MVCLST). MVCLST first builds on two data views using gene expression profiles, cell space coordinates, and image features. Then it employs four different encoders to capture the common and private features of the two views. The model employs a contrastive learning loss to encourage effective interaction between the two views and ensure feature consistency. The shared and private features from both views are fused using corresponding decoders. Finally, the model employs the Leiden algorithm for downstream clustering of the learned features. We test the MVCLST method on a human dorsolateral prefrontal cortex dataset. The results show that MVCLST outperforms other state-of-the-art methods in most cases. Additionally, the clusters identified by MVCLST align closely with manual annotations and established neuroscience definitions. © 2023 IEEE.

关键词： contrast learning multiview learning spatial transcriptome data clustering

来源：评论

学校读者我要写书评

暂无评论

Parks-McClellan Algorithm-Based Active Damping Strategy Applied to Grid-Connected Inverters

Parks-McClellan Algorithm-Based Active Damping Strategy Appl...

引用

IEEE Annual Southern Power Electronics Conference (SPEC)

作者： José de Arimatéia O. Filho Gabriel Lucas Bressanini Tiago Davi Curi Busarello Luis De Oro Arenas Paulo Fernando Silva Helmo Kelis Morales Paredes Group of Automation and Integratd Systems (GASI) São Paulo State University (Unesp) Sorocaba Brazil Department of Control Automation and Computing Engineering Federal University of Santa Catarina (UFSC) Blumenau Brazil

In recent years, grid-connected inverters have gained wide prominence, primarily attributed to the surge in distributed energy resources. To ensure the reliable operation of these inverters, it is crucial to adequately damp the resonance peak of the LCL filter at the inverter output. By achieving this, the grid-connected inverter guarantees the system's stability while minimizing the harmonic content in the current injected into the distribution grid. To address this issue, this paper proposes the utilization of digital differentiators in conjunction with optimized wideband differentiators, which are designed using the Parks-McClellan (PM) algorithm. These differentiators are applied specifically to the LCL filter capacitor voltage to dampen the resonance peak effectively. Simulation results univocally demonstrate the effectiveness of the proposed approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A reinforcement learning and predictive analytics approach for enhancing credit assessment in manufacturing

Decision Analytics Journal

引用

Decision Analytics Journal 2025年 15卷

作者： Razaque, Abdul Beishenaly, Aliya Kalpeyeva, Zhuldyz Uskenbayeva, Raisa Nikolaevna, Moldagulova Aiman Department of Software Engineering & AI School of Computing Gachon University Seongnam-si South Korea Department of Software Engineering Institute of Automation and Information Technologies Satbayev University Kazakhstan Department of Computer Engineering International Information Technology University (IITU) Almaty Kazakhstan

The fundamental issue with a credit system for manufacturers and importers of commodities is inefficient credit assessment. Traditional techniques frequently produce inaccurate risk assessments and credit scores, resulting in financial losses for lenders, missing business growth possibilities, and less favorable client conditions. To overcome this issue, a comprehensive credit assessment scoring system should be implemented to increase importers’ confidence. The article proposes a predictive-based reinforcement learning (PRL) model to help manufacturers and importers acquire more accurate and dependable credit scores while avoiding default risk. Furthermore, the proposed PRL model enhances decision-making, system efficiency, and risk-tolerant financial conditions. To attain these cutting-edge objectives, the proposed PRL model combines three algorithms. Algorithm 1 collects and aggregates data to indicate areas for improvement if credit scoring is poor. Algorithm 2 uses reinforcement learning to validate and enhance bank scores. Algorithm 3 focuses on predictive modeling for bank scoring, ensuring that the credit decision-making system is operational and constantly improving. Furthermore, reinforcement learning leverages the features from local interpretable model-agnostic explanations (LIME) and shapely additive explanations (SHAP) to generate locally reliable explanations and attribute the contribution of each feature for determining the output of the model. The Python platform tests the proposed PRL to achieve the objectives. Based on the results, The PRL model markedly enhances credit assessment precision, achieving an accuracy of over 99.5%, which outstrips current methodologies such OCLA (96.12%), PSML (84.12%), and EMPCC (91.67%). Furthermore, the PRL model augments leverage ratios, rising from 2.75% in 2015 to 3.36% in 2024.5, and increases accounts receivable turnover from 4.38% in 2015 to 7.4% in 2024.5, surpassing alternative credit evaluation methodologi

关键词： Financial analytics Intelligent credit systems Machine learning Manufacturing Predictive analytics Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Electric Motor Designs: Traditional Steel Laminations vs. Soft Magnetic Composite Materials

Comparative Analysis of Electric Motor Designs: Traditional ...

引用

International Conference on Electrical Machines, ICEM

作者： Branko Ban Anton Kersten Stefan Skoog Lars Sjöberg Stjepan Stipetić Tushar Batra Torquery Consulting Göteborg Sweden Department of Electrical Engineering Univeristy West Trollhättan Sweden Alvier Mechatronics Helsingborg Sweden Department of Electric Machines Drives and Automation Faculty of electrical engineering and computing (FER) University of Zagreb Zagreb Croatia

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

This paper presents a comparative analysis of electric machine designs for vehicle traction using traditional steel laminations versus soft magnetic composite (SMC) materials in four radial flux magnetic topologies: Rare-earth interior permanent magnet synchronous machine (IPM), wound field synchronous machine (WFSM), spoke-ferrite permanent magnet synchronous machine (SP-FER), and induction machine (IM). In total, 32 machine variants are evaluated considering different materials, and they are critically evaluated against a reference IPM traction machine with regards to performance, material cost and environmental impact. Results show that while the IPM design remains superior in performance for a fixed geometry, the WFSM and SP-FER offer significant environmental advantages. The WFSM emerges as the most eco-friendly option, while the SP-FER represents a balanced choice considering environmental impact, durability, production simplicity, and inverter complexity. This study highlights the potential of SMC materials compared to steel laminations in reducing costs (16 % to 29 %) and CO2-eq. emissions 21 % to 38 % in electric motor manufacturing without significantly compromising on performance, making it a viable alternative in automotive applications.

关键词： Permanent magnet machines Magnetic flux Costs Torque Lamination Automotive applications Magnetic analysis Steel Soft magnetic materials Electric motors

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Dynamic Event-Triggered Sliding-Mode Heading Control for Unmanned Surface Vehicles with Uncertainties

Data-Driven Dynamic Event-Triggered Sliding-Mode Heading Con...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Huarong Shan, Jinjun Li, Xing Yu, Hongnian School of Internet of Things Engineering Jiangnan University Wuxi214122 China York University Department of Earth and Space Science and Engineering TorontoONM3J 1P3 Canada School of Electrical Engineering and Intelligentization Dong-guan University of Technology Dongguan523000 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110819 China School of Computing Engineering and the Built Environment Edinburgh Napier University EdinburghEH10 5DT United Kingdom

ISBN: (纸本)9781665410205

This paper investigates a data-driven dynamic event-triggered sliding mode heading control problem for un-manned surface vehicles with uncertain dynamics models. First, a virtual sensor is introduced to establish a compact dynamic linearization model for the unmanned surface vehicle. Then, a dynamic event-triggered scheme is developed to alleviate the communication burden. Moreover, a sliding mode surface is designed, and a data-driven dynamic event-triggered sliding mode heading control approach is formulated. Finally, rigorous mathematical proofs are given, and several simulations demon-strate the effectiveness and superiority of the proposed method compared to existing approaches. © 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

Examining the Impact of Muscle-Electrode Distance in sEMG Based Hand Motion Recognition 16th

Examining the Impact of Muscle-Electrode Distance in sEMG Ba...

引用

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Shi, Jinwei Liu, Mingchun Fang, Yinfeng Yu, Jiahui Gao, Hongwei Ju, Zhaojie School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China School of Telecommunication Engineering Hangzhou Dianzi University Hangzhou310000 China Department of Biomedical Engineering Zhejiang University Hangzhou310027 China Innovation Center for Smart Medical Technologies & Devices Binjiang Institute of Zhejiang University Hangzhou310053 China School of Computing University of Portsmouth PortsmouthPO13HE United Kingdom

ISBN: (纸本)9789819964888

There are several factors that affect the sEMG signal during the process from its generation to its acquisition by sEMG devices. In this study, we tried to explain the physiological functional relationship between sEMG signals and muscles and between muscles and gestures in the human right forearm to increase confidence in the application of artificial intelligence in the medical field. For this purpose, we simulated the muscle and electrode positions with a 3D model to calculate their distance relationship, designed a cuff based on this model, and considered the effect of different distance solving methods on gesture recognition. The results showed that the highest accuracy of 93.95% was achieved for gesture recognition with the center of gravity method to find the electrode-to-muscle distance when the ratio of muscle electrode distance to the number of nerve muscle branches was 1:0.1. It is explained that the distance factor is the main factor affecting the recognition of sEMG signals, and an appropriate increase in the muscle length or neuromuscular branch number factor will play a positive role in the accuracy. The visualization of muscle activation further verifies and explains the relationship between sEMG signals and muscles, which makes the rehabilitation training more scientific and effective. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Muscle

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：