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International Conference on Sustainable Technology and Advanced Computing in electrical engineering, ICSTACE 2021

作者： Islam, Noorul Nat, Aslam Khan, Rashid Ahmed Department of Electrical Engineering ZH College of Engineering and Technology Aligarh Muslim University Aligarh202002 India Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy Department of Electrical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan

ISBN: (纸本)9789811943638

Energy has become an integral part of our life. The fossil fuel present in the environment is very much limited. On the other hand, fossil fuel emits harmful gases such as carbon dioxide, Chlorofluorocarbon (CFC), carbon monoxide, and others which harmed flora and fauna. Therefore, the concern for renewable energy application has become more vital due to the depletion of fossil fuels, rising global warming, and increased consumption of energy. Renewable energy aims to reduce pollution levels, enhancing the local economy and community sustainability. Solar energy is the most promising alternative energy source since it has various advantages over other renewable energy sources. The sun is an unquenchable source of energy capable of addressing all energy requirements of humankind. The solar energy concept has been around for a long time, and technological advancements will make it endure for a longer period. The PV-Effect is a mechanism that can produce an electric current when sunlight strikes the limiting layer of semiconductor materials. A photovoltaic (PV) system is a semiconductor device that produces electricity when exposed to luminosity. A PV module is made up of several solar cells that are coupled in parallel and series. This paper provides an extensive study of advancements in energy extraction techniques from a solar panel, analysing solar PV systems under diverse circumstances. PV technology is hastily evolving compared to alternative renewables, consequently leading to the Building Integrated Photovoltaics (BIPV) systems playing a significant role in the generation of electrical energy. BIPV system is a preferred choice as a building integrated solar energy storage system. It has been categorised into three subparts: Grid-connected BIPV system, BIPV system with a solar battery, and PV-Trombe wall. The BIPV mechanism simultaneously acts as a material for the envelope of the building and power extraction from. © 2022, The Author(s), under exclusive license

关键词： Fossil fuels

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Multi-agent Deep Reinforcement Learning Based Multi-objective Charging control for Electric Vehicle Charging Station 7th

Multi-agent Deep Reinforcement Learning Based Multi-objectiv...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Random Forest Regression for Battery State-of-Health Estimation Based on Unsupervised Transfer Component Analysis Domain Adaptation

Random Forest Regression for Battery State-of-Health Estimat...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Tian, Jilun Zhang, Jiusi Huangy, Congsheng Chowz, Mo-Yuen Luo, Hao Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan North Carolina State University Department of Electrical and Computer Engineering RaleighNC27606 United States

ISBN: (纸本)9781728119489

Machine learning is an useful approach estimating the state-of-health (SOH) of the lithium-ion batteries and had been successfully implemented on battery management systems (BMS). However, the SOH estimation accuracy of the machine learning relies highly on the similarity of training dataset and battery data of estimation. In other words, the machine learning approach may fail if the battery of estimation is operated in a different condition from the condition set for collecting the training dataset. This paper aims on solving such a problem by proposing a transfer component analysis-random forest regression (TCA-RF) approach. The robustness of this proposed approach is ensured by the random forest regression, which is an ensemble learning approach. The generalization of this proposed approach is enhanced by transfer component analysis since it achieves the domain adaption with well transformation of features between two datasets. Two battery ageing datasets collected in different operating conditions are selected in this paper to validate the success of the proposed work, where these two datasets are collected by the Center for Advanced Life Cycle engineering (CALCE) and the National Aeronautics and Space Administration (NASA) Prognostics Center of Excellence (PCoE). The proposed work is further compared with multiple commonly adopted intelligent algorithms to showcase the high performance of the proposed work. The experimental results shows that the proposed TCA-RF approach has a better accurate SOH estimation comparing to other estimation algorithms by 2% to more 50%. © 2022 IEEE.

关键词： Lithium-ion batteries

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Modeling and Simulation of Two Axes Gimbal Using Fuzzy control

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computers, Materials & Continua 2022年第7期72卷 93-107页

作者： Ayman A.Aly Mohamed O.Elhabib Bassem F.Felemban B.Saleh Dac-Nhuong Le Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Control and Mechatronics Division School of Electrical EngineeringUTMJohor Bahru81300Malaysia Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

The application of the guided missile seeker is to provide stability to the sensor’s line of sight toward a target by isolating it from the missile motion and *** main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling *** paper is started by deriving the mathematical model for gimbals motion using Newton’s second law,followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/***,a Mamdani-type fuzzy and a Proportional-Integral-Derivative(PID)controllers were designed using MATLAB *** performance of both controllers was evaluated and tested for different types of input *** simulation results showed that self-tuning fuzzy controller provides better performance,since no overshoot,small steady-state error and small settling time compared to PID controller.

关键词： Gimbal system self-tuning fuzzy proportional-integral-derivative(PID)control cross coupling

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Multiphase LLC Resonant Converter with Natural Current Sharing and Phase-Shedding

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IEEE Transactions on Industry Applications 2025年

作者： Ahmad, Ubaid Giral, Roberto Olalla, Carlos Sangwongwanich, Ariya Davari, Pooya Blaabjerg, Frede Universitat Rovira i Virgili Països Catalans Department of Electrical Electronics and Automatic Control Engineering School of Electrical and Computer Engineering Catalonia Tarragona26 43007 Spain Aalborg University Department of Energy Aalborg Ost9220 Denmark

The multiphase LLC converter is commonly used for high-power and high step-down applications. However, the tolerances in the tank circuit parameters cause uneven current sharing (CS), reducing system reliability. Additionally, phase-shedding (PS) can improve converter efficiency at partial load by turning-OFF phases. This paper proposes a multiphase input-parallel output-parallel LLC resonant converter with a common inductor-capacitor branch, with the objective to achieve excellent CS and phase-shedding at the same time. Thanks to the shared branch, current-sharing is natural, and phase-shedding is realized without affecting the operating point. With fewer passive comp- onents and a simple phase connection, the design offers low-cost, high-power density, and improved light-load efficiency compared to existing solutions. Detailed analysis shows improved CS on both the primary and secondary sides, when compared to previous approaches. Simulation and experimental results for the proposed two-phase LLC resonant converter validate the analysis and illustrate the effectiveness of the CS and PS capabilities. At the rated load of 800 W, CS error is 2.48% on the primary side and 2.0% on the secondary side. Phase-shedding improves efficiency by 3.60% at 50% load and 6.82% at 25% load. © 1972-2012 IEEE.

关键词： Resonant converters

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Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao LU Lan GAO Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China Department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： Path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries 13

Exponential Weighted Moving Average-Based Variational Mode D...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wu, Penghao Tao, Hongfeng Tian, Engang Yin, Tangwen Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350361674

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods. © 2024 IEEE.

关键词： Variational mode decomposition

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Towards experimental insight into magnetic flux distribution within the air gap of permanent magnet synchronous drive

Towards experimental insight into magnetic flux distribution...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Hubert Milanowski Adam Krzysztof Piłat Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH University of Krakow Krakow Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

This report explores the experimental identification of magnetic flux density within the motor air gap, focusing on the development of a robot-based approach to automate the scanning procedure. Emphasis is placed on analyzing the distribution of magnetic flux within the motor’s spatial air gap, as well as the amplification of harmonics resulting from changes in air gap orientation. Drawing upon experimental findings, a model is proposed to illustrate the three-dimensional distribution of magnetic flux within the gap.

关键词： Solid modeling Magnetic flux density Automation Atmospheric modeling Air gaps Rotors Drives

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Nonsingular Fast Terminal Sliding Mode Attitude control Design for a Coaxial Tilt-Rotor UAV

Nonsingular Fast Terminal Sliding Mode Attitude Control Desi...

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SICE Annual Conference

作者： Zheng Hou Longlong Chen Zongyang Lv Yuhu Wu Huijuan Song Man Wang School of Control Science and Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

This paper proposes an attitude controller utilizing the sliding mode technique for a coaxial tilt-rotor unmanned aerial vehicle (CTRUAV) in the presence of external disturbances. The CTRUAV features two servos that empower two pairs of coaxial rotors to tilt independently, along with a rear rotor. This sophisticated configuration sets it apart from regular unmanned aerial vehicles (UAVs) and imposes stringent requirements on the attitude controller design. A nonsingular fast terminal sliding mode controller (NFTSMC) is designed to achieve high speed, accuracy, and robust attitude tracking performance to address these challenges. The finite-time convergence property of NFTSMC is theoretically proved, and the singularity issue is addressed. The effectiveness of the developed control system is validated through comparative simulations and real-time experiments.

关键词： Accuracy Attitude control Rotors Autonomous aerial vehicles control systems Real-time systems Iron Servomotors Convergence

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A Tube-Based Reinforcement Learning Approach for Optimal Motion Planning in Unknown Workspaces

A Tube-Based Reinforcement Learning Approach for Optimal Mot...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this work, a tube-based nearly optimal solution to motion planning in unknown workspaces is presented. The advantages of reactive motion planning are combined with a Policy Iteration Reinforcement Learning scheme to yield a novel solution for unknown workspaces that inherits provable safety, convergence and optimality. Moreover, in simply-connected workspaces, our method is proven to asymptotically provide the globally optimal path. Our method is compared against a provably asymptotically optimal RRT ⋆ method, as well as a relevant reactive method and provides satisfactory performance, closely matching or outperforming the former.

关键词： Reinforcement learning Planning Safety Robotics and automation Convergence

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