检索结果-内蒙古大学图书馆

Data-driven finite-time adaptive attitude tracking control for spacecraft

Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

来源：评论

学校读者我要写书评

暂无评论

Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

引用

Computers, Materials & Continua 2023年第4期75卷 183-196页

作者： Samah Alshathri Ezz El-Din Hemdan Walid El-Shafai Amged Sayed Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Energy Engineering College of Engineering&TechnologyArab Academy for Science Technology&Maritime TransportSmart Village CampusEgypt

In recent years, Digital Twin (DT) has gained significant interestfrom academia and industry due to the advanced in information technology,communication systems, Artificial Intelligence (AI), Cloud Computing (CC),and Industrial Internet of Things (IIoT). The main concept of the DT isto provide a comprehensive tangible, and operational explanation of anyelement, asset, or system. However, it is an extremely dynamic taxonomydeveloping in complexity during the life cycle that produces a massive amountof engendered data and information. Likewise, with the development of AI,digital twins can be redefined and could be a crucial approach to aid theInternet of Things (IoT)-based DT applications for transferring the data andvalue onto the Internet with better decision-making. Therefore, this paperintroduces an efficient DT-based fault diagnosis model based on machinelearning (ML) tools. In this framework, the DT model of the machine isconstructed by creating the simulation model. In the proposed framework,the Genetic algorithm (GA) is used for the optimization task to improvethe classification accuracy. Furthermore, we evaluate the proposed faultdiagnosis framework using performance metrics such as precision, accuracy,F-measure, and recall. The proposed framework is comprehensively examinedusing the triplex pump fault diagnosis. The experimental results demonstratedthat the hybrid GA-ML method gives outstanding results compared to MLmethods like LogisticRegression (LR), Na飗e Bayes (NB), and SupportVectorMachine (SVM). The suggested framework achieves the highest accuracyof 95% for the employed hybrid GA-SVM. The proposed framework willeffectively help industrial operators make an appropriate decision concerningthe fault analysis for IIoT applications in the context of Industry 4.0.

关键词： Automated fault diagnosis control system ML AI CC IIoT digital twins genetic algorithm GA-ML technique

来源：评论

学校读者我要写书评

暂无评论

Hybrid Digital-Analog Semantic Communications

引用

IEEE Journal on Selected Areas in Communications 2025年第7期43卷 2478-2492页

作者： Xie, Huiqiang Qin, Zhijin Han, Zhu Letaief, Khaled B. Jinan University College of Information Science and Technology Guangzhou China Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Space Network and Communications Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China University of Houston Department of Electrical and Computer Engineering Houston United States The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

Digital and analog semantic communications (SemCom) face inherent limitations such as data security concerns in analog SemCom, as well as leveling-off and cliff-edge effects in digital SemCom. In order to overcome these challenges, we propose a novel SemCom framework and a corresponding system called HDA-DeepSC, which leverages a hybrid digitalanalog approach for multimedia transmission. This is achieved through the introduction of analog-digital allocation and fusion modules. To strike a balance between data rate and distortion, we design new loss functions that take into account long-distance dependencies in the semantic distortion constraint, essential information recovery in the channel distortion constraint, and optimal bit stream generation in the rate constraint. Additionally, we propose denoising diffusion-based signal detection techniques, which involve carefully designed variance schedules and sampling algorithms to refine transmitted signals. Through extensive numerical experiments, we will demonstrate that HDA-DeepSC exhibits robustness to channel variations and is capable of supporting various communication scenarios. Our proposed framework outperforms existing benchmarks in terms of peak signal-to-noise ratio and multi-scale structural similarity, showcasing its superiority in semantic communication quality. © 1983-2012 IEEE.

关键词： Digital communication systems

来源：评论

学校读者我要写书评

暂无评论

Event-triggered control of nonlinear systems under deception and Denial-of-Service attacks 63

Event-triggered control of nonlinear systems under deception...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Seifullaev, Ruslan Teixeira, Andre M. H. Ahlen, Anders Uppsala University Division of Systems and Control Department of Information Technology Sweden Uppsala University Division of Signals and Systems Department of Electrical Engineering Sweden

ISBN: (纸本)9798350316339

We address the problem of event-triggered networked control of nonlinear systems under simultaneous deception and Denial-of-Service (DoS) attacks. By DoS attacks, we refer to disruptions in the communication channel that prevent sensor measurements from reaching the controller. When the system undergoes a deception attack, the controller receives a modified output, deviating from the sensor's original measurement. We implement the input delay approach and the Lyapunov-Krasovskii technique to obtain sufficient conditions, expressed in terms of linear matrix inequalities (LMIs), that characterize the duration of the DoS interruptions under which input-to-state stability (ISS) of the closed-loop system is preserved. Furthermore, we explore scenarios involving simultaneous attacks, where the DoS is modeled as a stochastic Bernoulli process. The closed-loop system is then considered as a stochastic impulsive system. In a similar manner, we derive conditions to ensure mean-square ISS for this case. A numerical example illustrates the efficiency of the results. © 2024 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Abnormal Data Identification and Reconstruction Based on Wind Speed Characteristics

引用

CSEE Journal of Power and Energy Systems 2025年第2期11卷 612-622页

作者： Mao Yang Tian Peng Wei Zhang Xin Su Chao Han Fulin Fan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China Department of Electronic and Electrical Engineering University of StrathclYdeGlasgow G11XWUnited Kingdom

High availability of wind power data is the basis for wind power research, but there are a large number of abnormal data in actual collected data, which seriously affects analysis of wind power law and reduces prediction accuracy. Measured power data of wind farm are analyzed, influence of wind speed fluctuation characteristics on wind power is discussed, and abnormal points are identified for data of different wind types. The Cluster-Based Local Outlier Factor (CLOF) algorithm based on K-means is used to identify outlier abnormal points, and conditional constraints based on physical background are used to identify accumulation abnormal points. Reconstructed data segment is divided according to fluctuation of wind speed. The Bidirectional Gate Recurrent Unit (BiGRU) model with wind speed as input reconstructs fluctuation segment data, and bi-directional weighted random forest model reconstructs stationary segment data. Based on analysis of measured data of a wind farm, results show the method can effectively identify various abnormal data, and complete high-quality reconstruction of data, thereby improving accuracy of wind power prediction.

关键词： Abnormal data bidirectional weighted random forest BiGRU CLOF reconstruction wind power prediction wind speed characteristics

来源：评论

学校读者我要写书评

暂无评论

Automated object recognition in high-resolution optical remote sensing imagery

引用

National Science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Converter-Fed Induction Motor Efficiency Measurements - IEC 60034-2-3

Converter-Fed Induction Motor Efficiency Measurements - IEC ...

引用

2024 International Conference on electrical Machines, ICEM 2024

作者： Tiihonen, Matias Karkkainen, Hannu Aarniovuori, Lassi Niemela, Markku Liu, Dong Barta, Jan Laboratory of Electrical Drives Technology LUT University Lappeenranta Finland Laboratory of Electrical Drives Technology LUT University Lahti Finland LUT University Laboratory of control engineering and digital systems Lappeenranta Finland Brno University of Technology Department of Power Electrical and Electronic Engineering Brno Czech Republic

ISBN: (纸本)9798350370607

Induction motors consume huge amount of energy, so their energy efficiency is an important topic. The efficiency determination methods of direct-on-line motors are mature and during the last decade efforts have been made to create a standardized way to also determine efficiency of converter-fed motors. Here the efficiency determination methods given in IEC 60034-2-3 are utilized using a modern induction motor with the rated power of 7.5 kW and compared with the sinusoidal supply results. In addition, the high frequency harmonic power is extracted from the measured active power and its behavior as a function of the frequency and torque is illustrated. © 2024 IEEE.

关键词： comparison of standard methods energy efficiency frequency converter Induction motor measurements standardization

来源：评论

学校读者我要写书评

暂无评论

Transient Angle Stability of Inverters Equipped with Robust Droop control

引用

CSEE Journal of Power and Energy Systems 2023年第2期9卷 659-670页

作者： Chen Qi Keyou Wang Qing-Chang Zhong Jin Xu Guojie Li Key Laboratory of Control of Power Transmission and Conversion Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIllinois60616USA

Transient angle stability of inverters equipped with the robust droop controller is investigated in this *** first,the conditions on the control references to guarantee the existence of a feasible post-disturbance operating point are ***,the post-disturbance equilibrium points are found and their stability properties are ***,the attraction regions of the stable equilibrium points are accurately depicted by calculating the stable and unstable manifolds of the surrounding unstable equilibrium points,which presents an explanation to system transient ***,the transient control considerations are provided to help the inverter ridethrough the disturbance and maintain its stability *** is shown that the transient angle stability is not a serious problem for droop controlled inverters with proper control settings.

关键词： Droop controlled inverter equilibrium point transient angle stability (un)stable manifold

来源：评论

学校读者我要写书评

暂无评论

Knowledge-reused transfer learning for molecular and materials science

引用

Journal of Energy Chemistry 2024年第11期98卷 149-168页

作者： An Chen Zhilong Wang Karl Luigi Loza Vidaurre Yanqiang Han Simin Ye Kehao Tao Shiwei Wang Jing Gao Jinjin Li National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai 200240China Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.

关键词： Machine learning Transfer learning Small data Molecule Material science

来源：评论

学校读者我要写书评

暂无评论

A Weighted Average Consensus Approach for Decentralized Federated Learning

引用

Machine Intelligence Research 2022年第4期19卷 319-330页

作者： Alessandro Giuseppi Sabato Manfredi Antonio Pietrabissa Department of Computer Controland Management EngineeringUniversity of Rome La SapienzaRome 00185Italy Department of Electrical Engineering and Information Technology University of Naples Federico ⅡNaples 80125Italy

Federated learning(FedL)is a machine learning(ML)technique utilized to train deep neural networks(DeepNNs)in a distributed way without the need to share data among the federated training *** was proposed for edge computing and Internet of things(IoT)tasks in which a centralized server was responsible for coordinating and governing the training *** remove the design limitation implied by the centralized entity,this work proposes two different solutions to decentralize existing FedL algorithms,enabling the application of FedL on networks with arbitrary communication topologies,and thus extending the domain of application of FedL to more complex scenarios and new *** the two proposed algorithms,one,called FedLCon,is developed based on results from discrete-time weighted average consensus theory and is able to reconstruct the performances of the standard centralized FedL solutions,as also shown by the reported validation tests.

关键词： Federated learning(FedL) deep learning federated averaging(FedAvg) machine learning(ML) artificial intelligence discrete-time consensus distributed systems.

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：