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Improved deterministic and stochastic models for simulating partial discharges in non‐conducting trees inside solid dielectrics

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High Voltage 2021年第1期6卷 82-94页

作者： Johnatan M.Rodríguez‐Serna Ricardo Albarracín‐Sánchez Department of Electrical and Electronic Engineering Automatic Controland Applied PhysicsSchool of Industrial Design and Engineering(ETSIDI)Universidad Politécnica de Madrid(UPM)MadridSpain Department of Electrical Engineering Universidad de AntioquiaMedellínColombia

electrical trees are defects originated and driven by partial discharges(PD)activity and this is the reason why their modelling and simulation are fundamental for the ageing mechanisms comprehension and diagnosis analyses of insulation systems compound by solid *** study presents a brief review of the different models implemented to simulate PD in electrical trees inside solid *** addition,an improved deterministic model as well as a stochastic model are presented,which allow predicting adequately the PD pulses distribution,in magnitudes and phase,for non‐conducting electrical trees of different shape and *** case studies were simulated and their results exhibit good agreement when compared with measurements presented in the *** is concluded that the main parameters that state the PD behaviour in trees are the inception and extinction voltage mag-nitudes,including their probability distributions,and the tree *** models can be used for prognosis analysis based on on‐line measurements.

关键词： solid conducting electrical

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Operation Optimization of Integrated Energy System Considering Demand Response and Carbon Trading

Operation Optimization of Integrated Energy System Consideri...

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International Conference on Power and Energy Technology (ICPET)

作者： Ruizhe Fan Xuecheng Li Jun Li School of Electrical and Control Engineering North China University of Technology Beijing China Department of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany

ISBN: (数字)9798350375855

ISBN: (纸本)9798350375862

Integrated energy system is a useful tool for achieving the"dual-carbon"goal. In order to explore the demand-side adjustable potential of the comprehensive energy system for lowering carbon emissions, this paper proposes an optimal operation model that accounts for demand response under a carbon trading mechanism. Initially, the demand response is classified into two categories based on the characteristics of the load response. Additionally, a carbon trading mechanism is built for the integrated energy system by allocating the carbon emission quotas for the system using the baseline technique, which is free of charge. The actual carbon emissions from the gas turbine and gas boiler are also taken into account. Ultimately, a low-carbon optimization operation model of the integrated energy system is established, with the goal of minimizing the total cost of energy purchase, carbon trading, and operation and maintenance. The suggested model's validity is then confirmed through four types of typical scenarios.

关键词： Costs systems operation Tariffs Emissions trading Carbon dioxide Demand response Resource management Optimization Turbines Load modeling

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Development of Aero AI for Initial Flight Shape Design of Small Fixed-Wing UAV

Development of Aero AI for Initial Flight Shape Design of Sm...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Yu-Lin Ye Shih-Ting Tseng Ching-Huei Huang Kun-Lin Tsai Department Automatic Control Engineering Feng Chia University Taichung Taiwan Electrical Engineering Tunghai University Taichung Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

We created Aero Artificial Intelligence (Aero AI), an innovative AI platform for optimal Unmanned Aerial Vehicle (UAV) flight shape design. Aero AI guides designers to select UAV shape parameters intuitively. It assembles an initial UAV model based on selected parameters for shape evaluation. Then, it utilizes Stanford University Unstructured (SU2) for aerodynamic analysis and employs AI for neural network deep learning to generate reliable aerodynamic parameters without extensive wind tunnel tests for design. Aero AI reduces reliance on wind tunnel tests, saves energy and resources, and expedites the shape design process. AI platforms have permeated human life at an expeditious pace in recent years. Aero AI furnishes instantaneous and personalized responses to aerodynamic parameters. The development of such platforms facilitates a diverse spectrum of aerodynamic configurations and designs from commonplace knowledge-based inquiries to intricate domain-specific topics. By employing natural language processing methodologies, user interrogatives and proffer corresponding resolutions are enabled. The Aero AI platform applies continuous learning algorithms to augment response accuracy and relevance. Being intelligent inquiry-based, ubiquitous applications across myriad domains are possible, including customer service provisioning on web-based platforms, educational instruction aids, enterprise knowledge management, and issue resolution paradigms.

关键词： Deep learning Analytical models Accuracy Shape Wind tunnels Predictive models Aerodynamics

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Dynamics Loads of the Automated Electric Drive for Moving FKM-500 Filter-Press Plates 5

Dynamics Loads of the Automated Electric Drive for Moving FK...

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5th IEEE International Conference on Modern electrical and Energy System, MEES 2023

作者： Khrebtova, Oksana Zachepa, Iurii Zachepa, Nataliia Nekrasov, Andriy Pavlo, Kvitash Hrytsai, Oleksandr Kremenchuk Mykhailo Ostrohradskyi National University Department of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Electrical Engineering Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Department of Jurisprudence Sciences Kremenchuk Ukraine

ISBN: (纸本)9798350359787

Operational loads have both static and dynamic characteristics. Dynamic loads occur during the operation of the considered mechanism, both during acceleration and deceleration periods, as well as during steady motion due to the movement of the moving element along an uneven path caused by the presence of the working environment on the elements over which the filter-press plates are moving. The dynamic loading is significant and affects the formation of plate-side displacements during their movement while performing the technological operation. Experimental studies of the load on the movement elements were conducted to determine optimal control modes for the filter-press plate movement mechanism, aiming to avoid overloading during stopping and filter jamming. To analyze the loading, discretization of random processes of the filter movement mechanism loading was performed. The sequence of calculating the statistical characteristics of the schematized dynamic process is presented. Based on experimental data, mathematical calculation of the results of schematization and the type of probability distribution law was carried out. To select the law that best reflects the experimental data distribution of load amplitudes, the Kolmogorov-Smirnov goodness-of-fit criterion was applied. According to the calculation results, it was found that the Weibull distribution law adequately reflects the distribution of amplitudes since its corresponding Kolmogorov-Smirnov criterion value is the smallest. © 2023 IEEE.

关键词： Dynamic loads

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Fine-tuning Myoelectric control through Reinforcement Learning in a Game Environment

arXiv

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arXiv 2024年

作者： Freitag, Kilian Karayiannidis, Yiannis Zbinden, Jan Laezza, Rita Department of Electrical Engineering Chalmers University of Technology Sweden Department of Automatic Control Lund University Sweden

Objective: Enhancing the reliability of myoelectric controllers that decode motor intent is a pressing challenge in the field of bionic prosthetics. State-of-the-art research has mostly focused on Supervised Learning (SL) techniques to tackle this problem. However, obtaining high-quality labeled data that accurately represents muscle activity during daily usage remains difficult. We investigate the potential of Reinforcement Learning (RL) to further improve the decoding of human motion intent by incorporating usage-based data. Methods: The starting point of our method is a SL control policy, pretrained on a static recording of electromyographic (EMG) ground truth data. We then apply RL to fine-tune the pretrained classifier with dynamic EMG data obtained during interaction with a game environment developed for this work. We conducted real-time experiments to evaluate our approach and achieved significant improvements in human-in-the-loop performance. Results: The method effectively predicts simultaneous finger movements, leading to a two-fold increase in decoding accuracy during gameplay and a 39% improvement in a separate motion test. Conclusion: By employing RL and incorporating usage-based EMG data during fine-tuning, our method achieves significant improvements in accuracy and robustness. Significance: These results showcase the potential of RL for enhancing the reliability of myoelectric controllers, of particular importance for advanced bionic limbs. See our project page for visual demonstrations: ***/view/bionic-limb-rl. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Trajectory Planning of Autonomous Mobile Robot using Model Predictive control in Human-Robot Shared Workspace 3

Trajectory Planning of Autonomous Mobile Robot using Model P...

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3rd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Chen, Jieming Chen, Xiang Liu, Steven The Hong Kong Polytechnic University Department of Electrical Engineering Hong Kong Hong Kong University of Kaiserslautern Institute of Control Systems Kaiserslautern Germany

ISBN: (纸本)9798350398410

This paper proposes an integrated framework of trajectory planning and control for autonomous mobile robots (AMRs) in an intra-logistic scenario, where humans and robots share the same indoor workspace. The proposed framework consists of perception and trajectory planning. To perceive human motion, information from the RGB-D camera is used to detect human positions. Then a model-based tracking approach is employed to track multiple people's motion and estimate their speed over a short time horizon. For trajectory planning, a Model Predictive control (MPC) based scheme is adopted to generate motor commands while taking into account energy efficiency, safety, and addressing human-aware proximity constraints. To convexify the nonlinear collision avoidance constraints, Sequential Convexification Programming is employed. The simulation and experimental results demonstrate that the proposed method can be implemented in real-time and efficiently avoid people in advance. © 2023 IEEE.

关键词： Model predictive control

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Towards Evaluating the Security of Wearable Devices in the Internet of Medical Things 11

Towards Evaluating the Security of Wearable Devices in the I...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Vaseghi, Yas Behara, Behnaz Delrobaei, Mehdi K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Systems and Control Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Biomedical Engineering Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Mechatronics Tehran Iran

ISBN: (纸本)9798350308105

The Internet of Medical Things (IoMT) offers a promising solution to improve patient health and reduce human error. Wearable smart infusion pumps that accurately administer medication and integrate with electronic health records are an example of technology that can improve healthcare. They can even alert healthcare professionals or remote servers during operational failure, preventing distressing incidents. However, as the number of connected medical devices increases, the risk of cyber threats also increases. Wearable medication devices based on IoT attached to patients' bodies are prone to significant cyber threats. Being connected to the Internet exposes these devices to potential harm, which could disrupt or degrade device performance and harm patients. To ensure patient safety and well-being, it is crucial to establish secure data authentication for internet-connected medical devices. It is also important to note that the wearability option of such devices might downgrade the computational resources, making them more susceptible to security risks. This paper implements a security approach to a wearable infusion pump. We discuss practical challenges in implementing security-enabled devices and propose initial solutions to mitigate cyber threats. © 2023 IEEE.

关键词： Wearable technology

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Diffusion-Based Environment-Aware Trajectory Prediction

arXiv

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arXiv 2024年

作者： Westny, Theodor Olofsson, Björn Frisk, Erik Department of Electrical Engineering Linköping University Sweden Department of Automatic Control Lund University Sweden

The ability to predict the future trajectories of traffic participants is crucial for the safe and efficient operation of autonomous vehicles. In this paper, a diffusion-based generative model for multi-agent trajectory prediction is proposed. The model is capable of capturing the complex interactions between traffic participants and the environment, accurately learning the multimodal nature of the data. The effectiveness of the approach is assessed on large-scale datasets of real-world traffic scenarios, showing that our model outperforms several well-established methods in terms of prediction accuracy. By the incorporation of differential motion constraints on the model output, we illustrate that our model is capable of generating a diverse set of realistic future trajectories. Through the use of an interaction-aware guidance signal, we further demonstrate that the model can be adapted to predict the behavior of less cooperative agents, emphasizing its practical applicability under uncertain traffic conditions. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Experimental Verification of Grid Inverter Operation in Urban Environment 11

Experimental Verification of Grid Inverter Operation in Urba...

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11th International Conference on electrical, Electronic and Computing engineering, IcETRAN 2024

作者： Petronijević, Milutin Radonjić, Ivana Veselić, Boban Dimitrijević, Marko Milosavljević, Ćedomir Pantić, Lana University of Niš Faculty of Electronic Engineering Power Engineering Department Niš Serbia University of Niš Faculty of Sciences and Mathematics Department of Physics Niš Serbia University of Niš Faculty of Electronic Engineering Control Systems Department Niš Serbia University of Niš Faculty of Electronic Engineering Department of Electronics Niš Serbia University of East Sarajevo Faculty of Electrical Engineering East Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350386998

This study offers experimental testing of commercial and laboratory inverters, utilized in a laboratory prototype of an urban microgrid. Operation of grid inverters supplied by PV arrays in urban environments, encounters challenges such as partial shading and soiling. Emulation of the current-voltage characteristics of PV arrays enables repeated and reliable testing of inverter operation under irregular supply conditions. It has been shown that finding the maximum power point can be challenging under conditions of partial shading and soiling. Additionally, meeting the grid quality standards for the delivered power represents a challenge. Satisfying these requirements can be achieved through careful design of LCL filters at inverter output terminals, but further improvement can be achieved only through an adequate selection of the primary controller. To further improve the quality of grid currents, the possibility of applying innovative control algorithms has been demonstrated for laboratory inverters. Application of sliding mode controllers, besides ensuring system robustness, can prevent overshoots and fault responses from the current protection circuit by introducing a specific anti-windup structure. © 2024 IEEE.

关键词： Sliding mode control

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Data-Driven Distributionally Robust System Level Synthesis

arXiv

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arXiv 2024年

作者： Micheli, Francesco Tsiamis, Anastasios Lygeros, John The Automatic Control Laboratory The Department of Information Technology and Electrical Engineering ETH Zürich Switzerland

We present a novel approach for the control of uncertain, linear time-invariant systems, which are perturbed by potentially unbounded, additive disturbances. We propose a doubly robust data-driven state-feedback controller to ensure reliable performance against both model mismatch and disturbance distribution uncertainty. Our controller, which leverages the System Level Synthesis parameterization, is designed as the solution to a distributionally robust finite-horizon optimal control problem. The goal is to minimize a cost function while satisfying constraints against the worst-case realization of the uncertainty, which is quantified using distributional ambiguity sets. The latter are defined as balls in the Wasserstein metric centered on the predictive empirical distribution computed from a set of collected trajectory data. By harnessing techniques from robust control and distributionally robust optimization, we characterize the distributional shift between the predictive and the actual closed-loop distributions, and highlight its dependency on the model mismatch and the uncertainty about the disturbance distribution. We also provide bounds on the number of samples required to achieve a desired confidence level and propose a tractable approximate formulation for the doubly robust data-driven controller. To demonstrate the effectiveness of our approach, we present a numerical example showcasing the performance of the proposed algorithm. © 2024, CC BY.

关键词： Robust control

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