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Annual Meeting Industrial and Commercial Power systems Technical Conference

作者： Alexandre F. M. Correia José M. B. Lopes A. Paulo Coimbra Pedro Moura Aníbal T. de Almeida Department of Electrical and Computer Engineering Institute of System and Robotics University of Coimbra Coimbra Portugal

The increasing frequency of natural disasters has led to situations where small towns and critical infrastructure, become isolated from the main utility grid. The microgrids’ ability to work autonomously from the utility grid presents a viable solution to this problem. Microgrid resiliency is the characteristic related to the capacity of a microgrid to minimize the impact of disruptive events and ensure that the power supply is maintained under a variety of adverse conditions. This is specially important for critical infrastructures such as hospitals, communications and military bases. The objective of this paper is to simulate strategies and propose an algorithm for the design and management of electric microgrids with a focus on resiliency towards critical and disaster situations. The proposed solutions will be simulated, using a building microgrid implemented in the University of Coimbra as a pilot. As a result of the work, the study presents an algorithm that efficiently manages loads of a microgrid in order to increase its resilience when the microgrid is isolated from the utility grid.

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Real-Time Implementation of Quadrotor UAV Control System Based on a Deep Reinforcement Learning Approach

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computers, Materials & Continua 2024年第12期81卷 4757-4786页

作者： Taha Yacine Trad Kheireddine Choutri Mohand Lagha Souham Meshoul Fouad Khenfri Raouf Fareh Hadil Shaiba Aeronautical Sciences Laboratory Aeronautical and Spatial Studies InstituteBlida 1 UniversityBlida0900Algeria Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Energy and Embedded Systems for Transportation Research Department ESTACA-LABMontigny-Le-Bretonneux78066France Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The popularity of quadrotor Unmanned Aerial Vehicles(UAVs)stems from their simple propulsion systems and structural ***,their complex and nonlinear dynamic behavior presents a significant challenge for control,necessitating sophisticated algorithms to ensure stability and accuracy in *** strategies have been explored by researchers and control engineers,with learning-based methods like reinforcement learning,deep learning,and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control *** paper investigates a Reinforcement Learning(RL)approach for both high and low-level quadrotor control systems,focusing on attitude stabilization and position tracking tasks.A novel reward function and actor-critic network structures are designed to stimulate high-order observable states,improving the agent’s understanding of the quadrotor’s dynamics and environmental *** address the challenge of RL hyper-parameter tuning,a new framework is introduced that combines Simulated Annealing(SA)with a reinforcement learning algorithm,specifically Simulated Annealing-Twin Delayed Deep Deterministic Policy Gradient(SA-TD3).This approach is evaluated for path-following and stabilization tasks through comparative assessments with two commonly used control methods:Backstepping and Sliding Mode Control(SMC).While the implementation of the well-trained agents exhibited unexpected behavior during real-world testing,a reduced neural network used for altitude control was successfully implemented on a Parrot Mambo mini *** results showcase the potential of the proposed SA-TD3 framework for real-world applications,demonstrating improved stability and precision across various test scenarios and highlighting its feasibility for practical deployment.

关键词： Deep reinforcement learning hyper-parameters optimization path following quadrotor twin delayed deep deterministic policy gradient and simulated annealing

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Learning good state and action representations for Markov decision process via tensor decomposition

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 5157-5209页

作者： Chengzhuo Ni Yaqi Duan Munther Dahleh Mengdi Wang Anru R. Zhang Department of Electrical & Computer Engineering Princeton University Laboratory for Information & Decision Systems Massachusetts Institute of Technology Electrical Engineering & Computer Science Department Massachusetts Institute of Technology Department of Biostatistics & Bioinformatics Duke University

The transition kernel of a continuous-state-action Markov decision process (MDP) admits a natural tensor structure. This paper proposes a tensor-inspired unsupervised learning method to identify meaningful low-dimensional state and action representations from empirical trajectories. The method exploits the MDP's tensor structure by kernelization, importance sampling and low-Tucker-rank approximation. This method can be further used to cluster states and actions respectively and find the best discrete MDP abstraction. We provide sharp statistical error bounds for tensor concentration and the preservation of diffusion distance after embedding. We further prove that the learned state/action abstractions provide accurate approximations to latent block structures if they exist, enabling function approximation in downstream tasks such as policy evaluation.

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Proposed Privacy Preservation Technique for Color Medical Images

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Intelligent Automation & Soft Computing 2023年第4期36卷 719-732页

作者： Walid El-Shafai Hayam A.Abd El-Hameed Noha A.El-Hag Ashraf A.M.Khalaf Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd El-Samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Nowadays,the security of images or information is very *** paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image ***,the secret medical image is encrypted using Advanced Encryption Standard(AES)***,the secret report of the patient is embedded into the encrypted secret medical image with the Least Signiﬁcant Bit(LSB)watermarking *** that,the encrypted secret medical image with the secret report is concealed in a cover medical image,using Kekre’s Median Codebook Generation(KMCG)***,the stego-image obtained is split into 16 ***,it is sent to the *** adopt this strategy to send the secret medical image and report over a network *** proposed technique is assessed with different encryption quality metrics including Peak Signal-to-Noise Ratio(PSNR),Correlation Coefﬁcient(Cr),Fea-ture Similarity Index Metric(FSIM),and Structural Similarity Index Metric(SSIM).Histogram estimation is used to conﬁrm the matching between the secret medical image before and after *** results demonstrate that the proposed technique achieves good performance with high quality of the received medical image and clear image details in a very short processing time.

关键词： LSB steganography AES algorithm KMCG algorithm

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Emergency Clinical Procedure Detection via Wearable Sensors 66th

Emergency Clinical Procedure Detection via Wearable Sensors

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66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022

作者： Baskaran, Prakash Heard, Jamison Adams, Julie A. Collaborative Robotics and Intelligent Systems Institute Oregon State University CorvallisOR United States Department of Electrical and Microelectronic Engineering Rochester Institute of Technology NY United States

Communicating a patient’s state accurately during transfer from emergency medical technicians to hospital personnel is crucial for optimal care. Prior work demonstrated automated algorithms that combined wearable sensors with video data from cameras to detect clinical procedures and improve this information transfer. However, incorporating video requires task- or environment-specific installation mechanisms, raises privacy concerns, and is susceptible to occlusion and image noise. The presented approach detects clinical procedures using wearable sensors (i.e., inertial and electrophysiological) only and the procedures’ subtasks to mitigate the sensors’ signal variability to provide clinical procedure detection. © 2022 by Human Factors and Ergonomics Society. All rights reserved.

关键词： Ergonomics

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Resilience-oriented Operation of Power Distribution Networks with Line Hardening and Comprehensive Reconfiguration Measures 14

Resilience-oriented Operation of Power Distribution Networks...

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14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Li, Zhengmao Shi, Zhao Ruan, Guangchun Lin, Yuzhang Zhao, Jin Aalto University School of Electrical Engineering Espoo Finland Nanyang Technological University School of Electrical and Electronic Engineering Singapore Massachusetts Institute of Technology Laboratory for Information & Decision Systems Boston United States New York University Department of Electrical and Computer Engineering New York United States Trinity College Dublin Department of Electronic and Electrical Engineering Dublin Ireland

ISBN: (纸本)9781665455541

With the frequent occurrence of extreme events like natural disasters and man-made attacks, the resilience concept is attracting worldwide research attention. Thus, this paper proposes a resilient operation model for the power distribution network (PDN) to recover load and limit economic loss to the greatest possible extent. First, the line hardening measure is applied to strengthen the PDN to avoid the serious breakdown of distribution lines. In addition, a comprehensive single commodity flow-based reconfiguration approach is used which not only sets the buses connecting generation sources but also those at the end of broken lines as the slack buses. Then, the radiality of PDNs can still be guaranteed after reconfiguration. The resilience-oriented operation problem can be originally formulated as a nonlinear programming one while efficient linearization methods are applied to reduce computational burdens. Hence, the operation problem is reformulated as a mixed-integer linear programming one which will enjoy favorable solution performances. Finally, case studies on an IEEE 33 PDN including comparison cases with traditional benchmarks are done to show the effectiveness of our method. © 2023 IEEE.

关键词： Hardening

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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Prognostics and System Health Management Conference (PHM)

作者： Congrui Cai Zhonghai Lu Embedded Systems Master Program School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Department of Electrical Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms.

关键词： Performance evaluation Semiconductor device modeling Recurrent neural networks Computational modeling Estimation Power electronics Data models

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Optimum Estimation of Coastal Currents Using Moving Vehicles

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Journal of Atmospheric and Oceanic Technology 2023年第12期40卷 1431-1441页

作者： Chen, Kuanyu Huang, Chen-Fen Zheng, Zhe-Wen Lin, Sheng-Fong Liu, Jin-Yuan Guo, Jenhwa Institute of Oceanography National Taiwan University Taipei Taiwan Department of Power Vehicle and Systems Engineering National Defense University Taoyuan Taiwan Department of Earth Science National Taiwan Normal University Taipei Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Electrical and Computer Engineering Tamkang University New Taipei City Taiwan Department of Engineering Science and Ocean Engineering National Taiwan University Taipei Taiwan

Ocean acoustic tomography (OAT) deploys most moored stations on the periphery of the tomographic region to sense the solenoidal current field. Moving vehicle tomography (MVT), an advancement of OAT, not only samples the region from various angles for improving the resolution of mapped currents but also acquires information about the ir-rotational flow due to the sampling points inside the region. To reconstruct a complete two-dimensional current field, the spatial modes derived from the open-boundary modal analysis (OMA) are preferable to the conventional truncated Fourier series since the OMA technique describes the solenoidal and irrotational flows efficiently in which all modes satisfy the coastline and open boundary conditions. Comparisons of the reconstructions are presented using three different representations of currents. The first two representations explain only the solenoidal flow: the truncated Fourier series and the OMA Dirichlet modes. The third representation, accounting for the solenoidal and irrotational flows, uses all the OMA modes. For reconstructing the solenoidal flow, the OMA representation with the Dirichlet modes performs better than the Fourier series. A large difference appears near the bay mouth, where the OMA-Dirichlet reconstruction shows a better fit to the uniform currents. However, considerable uncertainty exists outside the bay mouth where the irrotational currents dominate. This can be improved by the third representation with the inclusion of the Neumann and boundary modes. The reconstruction results using field data were validated against the acoustic Doppler current profiler (ADCP) measurements. Additionally, incorporating constraints from ADCP measurements enhances the accuracy of the reconstruction. © 2023 American Meteorological Society.

关键词： Modal analysis

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FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALYSIS OF SIMULATION AND REAL-WORLD RESULTS 12th

FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALY...

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12th International Conference on Environmental engineering, ICEE 2023

作者： Klemenčič, Mitja Španer, Marijan Lep, Marjan Moharić, Matej Department of Transportation Engineering Faculty of Civil Engineering Transportation Engineering and Architecture University of Maribor Smetanova 17 Maribor Slovenia Laboratory for Power Electronics Institute of Robotics Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor Slovenia

This paper presents a study of the energy consumption of a full electric bus charged at a fast-charging station with pantographs in the city of Maribor. The results of simulated and real tests on the PT line 6 are compared and analysed. The partly electrified PT line 6 provides insights on comparison between simulated energy consumption and re-al-life energy consumption, charging time and reliability of charging. The results reveal that the simulation considered several important factors like real life turnaround time, driving cycle, regenerative braking, charging time, peak hour charging time, heating/cooling systems, full passenger load as important and critical to identify the appropriate concept for charging. Technical and operational errors were identified in real world, due to connectivity failures or driver errors in positioning the vehicle, which were not considered in the simulation. The real-world data and procedure for selection of the most appropriate charging technology represent a good basis for full electrified Public Transport in Maribor. © 2023 The Author(s). Published by Vilnius Gediminas Technical University.

关键词： Electric buses

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Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Conformal Decision Theory: Safe Autonomous Decisions from Im...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jordan Lekeufack Anastasios N. Angelopoulos Andrea Bajcsy Michael I. Jordan Jitendra Malik Department of Statistics UC Berkeley Department of Electrical Engineering and Computer Science UC Berkeley Robotics Institute Carnegie Mellon University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian predictions, to calibrating autonomous manufacturing to exhibit high throughput and low error, to the choice of trusting a nominal policy versus switching to a safe backup policy at run-time. The decisions produced by our algorithms are safe in the sense that they come with provable statistical guarantees of having low risk without any assumptions on the world model whatsoever; the observations need not be I.I.D. and can even be adversarial. The theory extends results from conformal prediction to calibrate decisions directly, without requiring the construction of prediction sets. Experiments demonstrate the utility of our approach in robot motion planning around humans and robot manufacturing.

关键词： Robot motion Pedestrians Machine learning algorithms Decision theory Switches Prediction algorithms Throughput

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