检索结果-内蒙古大学图书馆

4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： Irawan, Elysa Nensy Yamashita, Ken-Ichiro Fujita, Goro Functional Control Systems Shibaura Institute of Technology Tokyo Japan Salesian Polythecnic Department of Electrical Engineering Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350395914

In recent years, research on hybrid Savonius-Darrieus has significant attention within the wind energy sector. According to earlier research, this hybrid can produce higher torque at low tip speed ratios than a solo Darrieus model. However, as tip speed ratio increase, hybrids tend to perform lower than solo Darrieus. This study introduces an innovative paradigm termed rotor switching theory. It suggests switching from hybrid to solo Darrieus rotation at higher tip speed ratio for the turbine. Current study is conducted experimentally using testing models of small hybrid Savonius-Darrieus and solo Darrieus turbines. The internal rotor consists of two stages of Savonius turbines with a 0.2 overlap and a bucket angle of 135°, each having two blades. The external rotor features a NREL S809 Darrieus airfoil with a 5 cm cord length and three blades. Outer radius is 10 cm and its height is 15.4 cm. The experiments are conducted within an open-circuit wind tunnel with the wind speed variations of 3 - 12 m/s. Based on the results, the intersection of the moment and power coefficient graphs for both the hybrid and solo Darrieus occurs at TSR 1.7. When reaching this condition, switching the turbine rotation state from hybrid to solo Darrieus can offer advantages. By employing this concept, the turbine will achieve an expected initial power coefficient that is 150% better than the solo Darrieus and a maximum power coefficient that is 21% greater than the hybrid model. © 2024 IEEE.

关键词： Windmill

来源：评论

学校读者我要写书评

暂无评论

Robust control and Unified Operation of Integrated Fuel Cell Electric Vehicle and Supercapacitor 25

Robust Control and Unified Operation of Integrated Fuel Cell...

引用

25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Eltoum, M. A Mohammed Jacknoon, Aman Khan, Khalid Khalid, Muhammad Control & Instrumentation Engineering Department Saudi Arabia Kfupm Electrical Engineering Department Dhahran31261 Saudi Arabia Irc For Sustainable Energy Systems Kfupm Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350340266

The slow response rate of fuel cells (FC) proves to hinder the progression of fuel cell hybrid electric vehicles (FCHEVs). In this paper, a unified robust nonlinear control technique is designed for FCHEV-integrated supercapacitors (SC). Therefore, the FCHEV's requirements can be systematically balanced between FC with high energy density and SC with high power density. Accordingly, the hybrid energy storage system enables better driving range as well as a comparatively lower weight than battery-based electric vehicles. The proposed control technique utilizes feedback linearization in combination with sliding mode control to mitigate the impact of system uncertainties with minimal tracking error. The efficacy is demonstrated based on the presented DC-bus voltage regulation, SC current, and FC current. © 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

Exploration of Unknown Environment using Deep Reinforcement Learning

Exploration of Unknown Environment using Deep Reinforcement ...

引用

2023 International Conference on Robotics and Automation in Industry, ICRAI 2023

作者： Ali, Asad Gul, Sarah Mahmood, Tallat Ullah, Anayat Control Automotive and Robotics Lab Rawalpindi Pakistan Balochistan University of IT Engineering and Management Sciences Department of Electrical Engineering Quetta Pakistan

ISBN: (纸本)9781665464727

Exploring the unknown environment is a very crucial task where human life is at risks like search and rescue operations, abandoned nuclear plants, covert operations and more. Autonomous robots could serve this task efficiently. The existing methods use uncertainty models for localization and map building to explore the unknown areas requiring high onboard computation and time. We propose to use Deep Reinforcement Learning (DRL) for the autonomous exploration of unknown environments. In DRL, the agent interacts with the environment and learns based on experiences (feedback/reward). We propose extrinsic and curiosity-driven reward functions to explore the environment. The curiosity-based reward function motivates the agent to explore unseen areas by predicting future states, while the extrinsic reward function avoids collisions. We train the differential drive robot in one environment and evaluate its performance in another unknown environment. We observe curiosity-driven reward function outperformed the extrinsic reward by exploring more areas in the unknown environment. The test results show the generalization capability to explore unknown environments with the proposed methods. © 2023 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Customer Attitudes Toward Circular Economy in the E-Waste Context: A Survey Assessing Sustainable Consumption Dynamics

引用

IEEE engineering management Review 2023年第4期51卷 28-45页

作者： Jabbour, Charbel Jose Chiappetta Colasante, Annarita D'Adamo, Idiano Rosa, Paolo Sassanelli, Claudio NEOMA Business School Department Information Systems Supply Chain and Decision Making Mont-Saint-AignanCedex 76130 France Unitelma Sapienza-University of Rome Department of Law and Economics Rome00161 Italy Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Politecnico di Milano Department of Management Economics and Industrial Engineering Milan20133 Italy Politecnico di Bari Department of Mechanics Mathematics and Management Bari70125 Italy

Waste from electrical and electronic equipment (WEEE) is a relevant concern in Europe. Even if relevant improvements have been made in terms of material recovery technologies and policy measures, there remains a significant gap between the amount of WEEE generated versus collected in the EU. This study is based on an online survey whose aim was to assess the attitude of students (i.e., individuals who dispose with a higher frequency electronic product) to buy/substitute three iconic product types (i.e., smartphones, notebooks, televisions), and their openness toward circular practices (i.e., recycling, reconditioning, reuse). Results have shown that: a) new products represent the greatest market share, b) reliability and quality were the most significant factors influencing the purchase decision in all product types, and c) circular premium was not recognized by students for any product type. From a social perspective, a responsible consumption pattern emerged, though a sustainability bias was evident with respect to products' residual value. From an economic perspective, these findings may inform companies about the orientation of young consumers and provide key insights for new business strategies. Results suggest that a proper waste management strategy also requires a behavioral change of people who should adopt it. © 1973-2011 IEEE.

关键词： Electronic Waste

来源：评论

学校读者我要写书评

暂无评论

Deepfake Detection Analysis Based on Video Face Analysis 19

Deepfake Detection Analysis Based on Video Face Analysis

引用

19th IEEE International Conference on Computer Science and Information Technologies, CSIT 2024

作者： Pitsun, Oleh Melnyk, Nazar Lipianina-Honcharenko, Khrystyna West Ukrainian National University Department of Computer Engineering Ternopil Ukraine West Ukrainian National University Department for Information-Computing Systems and Control Ternopil Ukraine

ISBN: (纸本)9798331542627

The article examines the detection of manipulation of multimedia content, in particular in the form of videos and photos. The concept of deepfake is considered, the means and technologies involved in deepfake are analyzed, current and promising methods of detecting and preventing fake multimedia content are evaluated. Approaches to the methods of creating fakes on videos with elements of manipulation of the human face are defined. Faceswap and Deepfakes Web are found to be the most powerful solutions used to generate deepfakes. An analysis of tools for detecting deepfakes on the face was carried out, which made it possible to highlight the main technologies, libraries, and datasets used to search for fakes. The DeepFake Detection Challenge (DFDC) Model, Forensically, and others have been found to have significant potential and sample size to accurately detect human-faced fakes. This paper proposes a generalized approach to the detection of deep fakes on the human face using machine learning and computer vision technologies © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Image-Based Fast Finite-Time Target Tracking control of Onboard Inertially Stabilized Camera Platform

引用

IEEE Transactions on Industrial Electronics 2024年第12期71卷 16409-16418页

作者： Sun, Xunhong Zhu, Wenwu Du, Haibo Chen, Weile Chen, Chih-Chiang Hefei University of Technology School of Electrical Engineering and Automation Hefei230009 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

In this article, we investigate the problem of fast finite-time target tracking control of the inertially stabilized platform (ISP) with a camera that mounted on a mobile robot. At first, the kinematics of the onboard ISP target tracking system is established by the geographic coordinate and pinhole camera model, which includes the state-dependent uncertainties and external disturbances. Then, based on the image information captured by camera, a continuous image-based fast finite-time control algorithm is designed for target tracking. Rigorous analysis proves that the target can be tracked at the center of camera's view in finite time in the absence of disturbances. In the presence of disturbances, the tracking error can converge to a region around the origin in finite time. Simulation and experimental comparisons are presented to confirm the efficiency of the proposed method. © 1982-2012 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Data-Driven LIDAR Feedforward Predictive Wind Turbine control

Data-Driven LIDAR Feedforward Predictive Wind Turbine Contro...

引用

2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Dinkla, Rogier Oomen, Tom Wingerden, Jan-Willem Van Mulders, Sebastiaan P. Delft University of Technology Delft Center for Systems and Control Faculty of Mechanical Engineering Mekelweg 2 Delft2628 CD Netherlands Eindhoven University of Technology Control Systems Technology Group Department of Mechanical Engineering Eindhoven5600 MB Netherlands

ISBN: (纸本)9798350335446

Light Detection and Ranging (LIDAR)-assisted Model Predictive control (MPC) for wind turbine control has received much attention for its ability to incorporate future wind speed disturbance information in a receding horizon optimal control problem. However, the growth of wind turbine sizes results in increasing system complexity and system interactions, and complicates the design of model-based controllers like MPC. Together with increasing data availability, this obstacle motivates the use of direct data-driven predictive control approaches like Subspace Predictive control (SPC). An SPC implementation is developed that both does not suffer from traditional, potentially detrimental closed-loop identification bias and incorporates past and future (not necessarily periodic) disturbance information. Simulations of the presented method for above-rated wind turbine rotor speed regulation using pitch control demonstrate the capabilities of the data-driven SPC algorithm for increasing degrees of wind speed disturbance information in the developed framework. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Collision avoidance and routing based on location access (CARLA) of mobile robots

引用

Neural Computing and Applications 2025年第9期37卷 6401-6430页

作者： ElSayyad, Shimaa Ezzat Saleh, Ahmed I. Ali, Hesham A. Saraya, M.S. Rabie, Asmaa H. Abdelsalam, Mohamed M. Computers Engineering Department MISR Higher Institute for Engineering and Technology Mansoura Round Road Mansoura City35516 Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Dean of Faculty of Artificial Intelligence Delta University for Science and Technology Gamasa Mansoura Egypt Faculty of Engineering Mansoura National University Gamasa Mansoura Egypt

The paper introduces a new path-planning robotic system methodology called Collision Avoidance and Routing based on Location Access (CARLA) for use in critical environments such as hospitals and crises where quick action and saving human lives are vital. The main focus of our framework is on accuracy and fast responses, such as delivering tools or items in a specific area while avoiding collisions with other robots and obstacles. CARLA is designed to provide quick responses during emergencies, unlike most existing algorithms that are integrated into site control units or distributed among mobile robots on-site. By being loaded onto a remote server node rather than individual robots, CARLA helps to conserve the robots' capabilities, hardware resources, and power consumption. Additionally, our system utilizes cloud computing and Fog servers technology to improve data transmission times between the cloud and smart devices, especially for applications with strict timing requirements like emergency response. The Fog platform is also leveraged to enhance on-site access to real-time interaction and location-based services by bringing processing power closer to the robots from far-off Cloud servers. CARLA has various applications, such as in factories and warehouses, where mobile robots need to be selected and directed by a central control system remotely. The proposed framework consists of three main modules: Robot Knowledge Module, Robot Selection Module, and Route Reservation Module, which will all be discussed in detail in this paper. The results of simulations using this framework show that the robots have improved flexibility and efficiency in terms of computing paths and successfully fulfiling requests without colliding, compared to traditional methods used in similar scenarios. © The Author(s) 2025.

关键词： Mobile robots

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

Voltage Quality Improvement for Hybrid Energy Storage of DC Microgrid 11

Voltage Quality Improvement for Hybrid Energy Storage of DC ...

引用

11th International Conference on Power and Energy systems engineering, CPESE 2024

作者： Mahmoud, Abdulrahman Babiker, Ahmed Mohamed, Mazen Ahmed, Ijaz Khalid, Muhammad Control and Instrumentation Engineering Department Saudi Arabia Department of Electrical Engineering Islamabad Pakistan Electrical Engineering Department Dhahran31261 Saudi Arabia KFUPM Interdisciplinary Research Center for Sustainable Energy Systems Saudi Arabia

ISBN: (纸本)9798350377439

DC microgrids (MGs) have recently garnered significant interest due to their efficient power conversion and simpler control systems compared to AC MGs. However, managing DC MGs presents specific challenges, especially when dealing with pulsed power loads and constant power loads, as both require rapid dynamic responses from the MG, impacting voltage quality. This paper introduces a novel control methods, including a highpass filter with model predictive control (MPC) for current distribution between the battery and supercapacitor (SC) and a neuro-fuzzy system, to address these issues. These methods adjust the SC's state of charge (SoC) following abrupt load changes and maintain its SoC within a predefined range to ensure continuous operation. Using the proposed feedback neuro-fuzzy technique, the MG can improve voltage quality and transient response, achieving results that are nearly identical to those of the MPC. Simulations conducted in MATLAB/Simulink confirm the effectiveness of this approach. © 2024 IEEE.

关键词： High pass filters

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：