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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Abbou, Hossam E.A. Benzoubir, Mohammed E. Hachemi, Ahmed Delassi, Abdelmoumene Arif, Salem Trabelsi, Mohamed Vahedi, Hani Bauer, Pavol Electrical Engineering Departement LACoSERE laboratory University of Amar Telidji Laghouat03000 Algeria Electrical Engineering Lab University of Kasdi Merbah Ouargla Algeria Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait City27235 Kuwait Department of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

ISBN: (纸本)9781665464543

This paper presents an innovative control strategy to enhance the stability of interconnected Microgrids (MGs) with low inertia and high penetration levels of Renewable Energies (REs). The proposed control strategy encompasses a new virtual droop control mechanism that emulates the primary control of synchronous generators for enhanced system stability. Additionally, a weighted Proportional-Integral (PI) controller is used to mitigate the adverse effects of measurement delays caused by Phase-Locked Loop (PLL) dynamics. Furthermore, a feedback integral loop is introduced to improve the efficiency and lifespan of Vanadium Redox Flow Batteries (VRFBs) enabling swift and precise power delivery while reducing steady-state errors. Finally, a new fractional-order virtual inertia control (VIC) is introduced to leverage the fractional derivatives and enhance the system's frequency response. The presented simulation results demonstrate the effectiveness of the proposed control approach in improving the frequency response and power exchange dynamics across interconnected MGs under various operating scenarios. © 2024 IEEE.

关键词： Microgrids

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SmokerViT: A Transformer-Based Method for Smoker Recognition

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computers, Materials & Continua 2023年第10期77卷 403-424页

作者： Ali Khan Somaiya Khan Bilal Hassan Rizwan Khan Zhonglong Zheng College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua321004China School of Electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China Department of Electrical Engineering and Computer Science Khalifa University of Science and TechnologyAbu Dhabi127788United Arab Emirates Key Laboratory of Intelligent Education of Zhejiang Province Zhejiang Normal UniversityJinhua321004China

Smoking has an economic and environmental impact on society due to the toxic substances it *** Neural Networks(CNNs)need help describing low-level features and can miss important ***,accurate smoker detection is vital with minimum false *** answer the issue,the researchers of this paper have turned to a self-attention mechanism inspired by the ViT,which has displayed state-of-the-art performance in the classification *** effectively enforce the smoking prohibition in non-smoking locations,this work presents a Vision Transformer-inspired model called SmokerViT for detecting ***,this research utilizes a locally curated dataset of 1120 images evenly distributed among the two classes(Smoking and NotSmoking).Further,this research performs augmentations on the smoker detection dataset to have many images with various representations to overcome the dataset size *** convolutional operations used in most existing works,the proposed SmokerViT model employs a self-attention mechanism in the Transformer block,making it suitable for the smoker classification ***,this work integrates the multi-layer perceptron head block in the SmokerViT model,which contains dense layers with rectified linear activation and linear kernel regularizer with L2 for the recognition *** work presents an exhaustive analysis to prove the efficiency of the proposed SmokerViT *** performance of the proposed SmokerViT performance is evaluated and compared with the existing methods,where it achieves an overall classification accuracy of 97.77%,with 98.21%recall and 97.35%precision,outperforming the state-of-the-art deep learning models,including convolutional neural networks(CNNs)and other vision transformer-based models.

关键词： Smoker recognition SmokerViT deep learning transformer for vision

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Complex-frequency waves:beat loss and win sensitivity

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Light(science & Applications) 2024年第2期13卷 181-183页

作者： Qingqing Cheng Tao L School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Department of Respiratory Diseases and Critical Medicine Quzhou Hospital Affiliated to Wenzhou Medical UniversityQuzhou324000China National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesNanjing UniversityNanjing210093China

Recent experiments have demonstrated that synthesized complex-frequency waves can impart a virtual gain to molecule sensing systems,which can effectively restore information lost due to intrinsic molecular *** enhancement notably amplifies the signal of trace molecular vibrational fingerprints,thereby substantially improving the upper limit of sensitivity.

关键词： thereby Complex limit

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Dual Ensemble Kalman Filter for Stochastic Optimal Control 63

Dual Ensemble Kalman Filter for Stochastic Optimal Control

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Joshi, Anant A. Taghvaei, Amirhossein Mehta, Prashant G. Meyn, Sean P. University of Illinois Urbana-Champaign Coordinated Science Laboratory Department of Mechanical Science and Engineering United States University of Washington Department of Aeronautics and Astronautics Seattle United States University of Florida Department of Electrical and Computer Engineering Gainesville United States

ISBN: (纸本)9798350316339

In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also one of our motivation. The main contribution is a simulation-based algorithm - dual ensemble Kalman filter (EnKF) - to numerically approximate the solution of these problems. The paper extends our previous work where the dual EnKF was applied in deterministic settings of the problem. The theoretical results and algorithms are illustrated with numerical experiments. © 2024 IEEE.

关键词： Wiener filtering

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Application of ANN and Equivalent electrical Circuit for Understanding the Power Transformer Frequency Response Analysis

Application of ANN and Equivalent Electrical Circuit for Und...

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2024 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2024

作者： Alwady, Ahmed Allawy Al-Ameri, Salem Mgammal Alamal College for Specialized Medical Science Medical Laboratory Techniques Department Karbala56001 Iraq Curtin University Malaysia Department of Electrical and Computer Engineering Miri98000 Malaysia

ISBN: (纸本)9798350357905

Frequency Response Analysis (FRA) is a well-known method approved and increases interest in performing electric power utility tests. FRA has become a recognized technology for detecting winding and core deformations in power transformers. The weakness of the FRA method is that there is no approved standard or guidelines to understand the measured results, which depends on individual knowledge. For further understanding of the FRA measurement, there are the lumped circuit approaches for power transformer fault analysis. The presented circuit approaches elements of the transformer, including windings and core, can be measured, or calculated. The challenge of identifying parameters for a power transformer equivalent circuit can be solved using frequency response analysis (FRA) and artificial neural networks (ANN). In this paper, the two techniques proposed and employed to extract the appropriate values of transformer circuit parameters that can simulate the identical measured response. The proposed technique is examined through its application on a three-phase transformer with 33/11 kV 500kV A. The FRA measurement was conducted using the end-to-end open-circuit test. The results show that FRA and ANN techniques can be used to identify transformer-equivalent circuit parameters. Furthermore, the proposed methods can be extended and used to estimate the parameters of a three-phase power transformer of different ratings. © 2024 IEEE.

关键词： Power transformers

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Position Measurement Based Slave Torque Feedback Control for Teleoperation Systems With Time-Varying Communication Delays

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 388-402页

作者： Xian Yang Jing Yan Changchun Hua Xinping Guan the Institute of Information Science and Engineering Yanshan University the Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004China IEEE the Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China

Bilateral teleoperation system is referred to as a promising technology to extend human actions and intelligence to manipulating objects *** the tracking control of teleoperation systems,velocity measurements are necessary to provide feedback ***,due to hardware technology and cost constraints,the velocity measurements are not always *** addition,the time-varying communication delay makes it challenging to achieve tracking *** paper provides a solution to the issue of real-time tracking for teleoperation systems,subjected to unavailable velocity signals and time-varying communication *** order to estimate the velocity information,immersion and invariance(I&I)technique is employed to develop an exponential stability velocity *** the proposed velocity observer,a linear relationship between position and observation state is constructed,through which the need of solving partial differential and certain integral equations can be ***,the mean value theorem is exploited to separate the observation error terms,and hence,all functions in our observer can be analytically *** the estimated velocity information,a slave-torque feedback control law is presented.A novel Lyapunov-Krasovskii functional is constructed to establish asymptotic tracking *** particular,the relationship between the controller design parameters and the allowable maximum delay values is ***,simulation and experimental results reveal that the proposed velocity observer and controller can guarantee that the observation errors and tracking error converge to zero.

关键词： Asymptotic stability bilateral teleoperation time-varying delay velocity observer

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Staggered Microstrip Grating Structure for Sheet-Beam TWTs 25

Staggered Microstrip Grating Structure for Sheet-Beam TWTs

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25th Joint IEEE International Vacuum Electronics Conference and 15th International Vacuum Electron Sources Conference, IVEC + IVESC 2024

作者： Marosi, Robert Zuboraj, Muhammed Capolino, Filippo University of California Department of Electrical Engineering and Computer Science IrvineCA United States Los Alamos National Laboratory Los AlamosNM United States

ISBN: (纸本)9798350348705

We introduce a simple geometry for slow-wave structures (SWSs) in sheet-beam traveling-wave tubes (TWTs). The staggered microstrip grating SWS is a space harmonic structure with geometry and bandwidth with analogous to the staggered vane SWS commonly used for sheet beam TWTs. The staggered microstrip grating TWT is designed to operate in V-band with a center frequency of 74 GHz and electron beam voltage of 20 kV. © 2024 IEEE.

关键词： Slow wave structures

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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control 63

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Broens, Yorick Butler, Hans Toth, Roland Asml Veldhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Hunren Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype. © 2024 IEEE.

关键词： Continuous time systems

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Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning 35

Microservice Deployment for Satellite Edge AI Inference via ...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yu, Zhiyong Cheng, Hei Victor Yang, Zhanpeng Liu, Xin Jiang, Yuning Zhou, Yong Shi, Yuanming ShanghaiTech University School of Information Science and Technology Shanghai201210 China Aarhus University Department of Electrical and Computer Engineering Denmark Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350362244

Artificial intelligence (AI) is critical in evolving 5G and developing 6G networks, running on edge devices, and solving resource management challenges. The burgeoning number of edge devices draws attention to the potential of low-earth orbit (LEO) satellite networks with their onboard computing capabilities for edge inference. This paper explores LEO scenarios where multiple remote sensing edge AI inference tasks concurrently process data from a single source. However, due to there being parts with the same functions between different AI applications, traditional monolithic edge AI architecture must be deployed repeatedly and falls short in efficiently harnessing the heterogeneous resources of LEO satellite networks. To solve this problem, we utilize the microservice architecture to decouple a single AI application into several independent microservices to reuse these same functions. However, due to the high latency caused by multiple microservices' communication, we need to design a deployment strategy to fully utilize resources to reduce the service latency. We present a microservice deployment model to minimize the total service latency across all AI applications and meet resource constraints with the constraints of hardware, energy, and memory limitations. This latency optimization problem is rewritten as a Markov decision process (MDP) to effectively deal with the challenge posed by the time-varying transmission rate caused by satellite mobility. To increase the training data utilization, we employ a Proximal Policy Optimization (PPO) based reinforcement learning algorithm to meet the dynamic environment challenge. Finally, we obtain a sub-optimal solution with minimal accuracy loss and an acceptable solution time. © 2024 IEEE.

关键词： Markov processes

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