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UKACC International Conference on control (control)

作者： Zezhi Tang J Anthony Rossiter George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

In this paper, the optimal control problem of uncertain nonlinear systems is considered. A nonlinear disturbance observer (NDO) is proposed to measure the lumped uncertainties present in the system. Disturbances that do not enter the same channel as the control signal, so-called mismatched disturbances, are difficult to reject directly within the control channel. To overcome the challenge, a generalized disturbance observer-based compensator is implemented to address the uncertainty compensation problem by attenuating its influence on the output channel. In real time, by augmenting the system states with the output tracking error, we develop a composite actor-critic reinforcement learning (RL) scheme for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving the Hamilton-Jacobi-Bellman (HJB) equation. Concurrent learning is applied in this article by using the recorded data of the known model of the system, in order to enhance the robustness of the system by canceling the influence of the probing signal. Simulation results demonstrate the effectiveness of the proposed scheme, offering an optimal solution for the output tracking problem in a second-order model with mismatched disturbances.

关键词： Uncertainty Simulation Measurement uncertainty Optimal control Reinforcement learning Mathematical models Robustness

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Incident indicators for freeway traffic flow models

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Communications in Transportation Research 2022年第1期2卷 66-74页

作者： Azita Dabiri Balazs Kulcsar Delft Center for Systems and Control Delft University of Technology2628 CNDelftthe Netherlands Department of Electrical Engineering Chalmers University of Technology41296GothenburgSweden

Developed in this paper is a traffic flow model parametrised to describe abnormal traffic *** large traffic networks,the immediate detection and categorisation of traffic incidents/accidents is of capital importance to avoid breakdowns,further ***,this claims for traffic flow models capable to capture abnormal traffic condition like ***,by means of proper real-time estimation technique,observing accident related parameters,one may even categorize the severity of ***,in this paper,we suggest to modify the nominal Aw-Rascle(AR)traffic model by a proper incident related *** proposed Incident Traffic Flow(ITF)model is defined by introducing the incident parameters modifying the anticipation and the dynamic speed relaxation terms in the speed equation of the AR *** modifications are proven to have physical ***,the characteristic properties of the ITF model is discussed in the paper.A multi stage numerical scheme is suggested to discretise in space and time the resulting non-homogeneous system of *** resulting systems of ODE is then combined with receding horizon estimation methods to reconstruct the incident ***,the viability of the suggested incident parametrisation is validated in a simulation environment.

关键词： Macroscopic traffic flow models Aw-Rascle model Traffic accidents Moving horizon PDE ODE Multi stage numerical scheme

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

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23rd International Conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Computationally Efficient Kalman Filter Framework for Intra-Frame Image Reconstruction with a Rolling Shutter Camera

Computationally Efficient Kalman Filter Framework for Intra-...

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IEEE International Conference on Image Processing

作者： Sabeethan Kanagasingham Andrew R. Mills Visakan Kadirkamanathan Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This paper addresses the problem of reconstructing image sequences from a rolling shutter camera-based thermal image acquisition system that integrates the image field over an exposure time. It proposes a novel approach to extend the distributed Kalman filtering framework for intra-frame reconstruction. This accounts for the exposure effect through a state-augmentation model, while respecting the row-byrow image acquisition process. Additionally, two alternative rolling shutter scan strategies: interlaced-x and random, are explored to mitigate delays in observing abrupt changes inherent in sequential rolling shutter scans. Simulation results demonstrate that the proposed approach effectively accommodates exposure and achieves reliable intra-frame reconstruction quality. The interlaced-x scan strategy, with x equal to the size of the image partition block, emerges as the preferred choice, highlighting improved performance in recovering from sudden events. The augmented distributed Kalman filter offers a scalable solution to enhance temporal resolution and overall reliability of thermal imaging of dynamic thermal processes.

关键词： Image resolution Simulation Thermal variables measurement Three-dimensional printing Size measurement Time measurement Steady-state

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A Power-Communication Co-Simulation Platform for Real-Time Microgrid Cyber Security Analysis

A Power-Communication Co-Simulation Platform for Real-Time M...

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Artificial Intelligence of Things and systems (AIoTSys), International Conference on

作者： Dongmeng Qiu Mengxiang Liu Xin Zhang Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (数字)9798331507886

ISBN: (纸本)9798331507893

The rapid digitalisation process in power system has greatly benefited the large-scale integration of distributed energy resources (DERs), essentially accelerating the progress towards net zero. However, numerous cyber attacks such as false data injection (FDI) attacks are impeding the normal control and operation activities. This paper aims to establish a real-time microgrid co-simulation platform to fully study the impacts of realistic attack events on micorgrid's control performance. Although there exist a large number of power-communication co-simulation platforms for the power system, they are designed to mainly provide validation services for control and operation algorithms and little attention has been paid to the cyber security. In the established microgrid platform, power and communication parts are simulated in Typhoon Hardware-in-the-loop(HIL) 602+ and EXata Network Simulator, respectively, and a dedicated synchronisation scheme is developed and embedded in Raspberry Pis to achieve master-slave data exchange between them. Based on the advanced cyber libraries provided by EXata, realistic FDI and packet drop attacks are mounted against the mapped communication links within EXata. The results indicate that these cyber attacks can severely influence the microgrid control performance including destabilising system states and specific state deviations, further demonstrating the necessity of deploying effective cyber-resilience enhancement mechanisms.

关键词： Tropical cyclones Prevention and mitigation Microgrids Real-time systems Main-secondary Libraries Power systems Synchronization Security Cyberattack

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Development of a Method of automatic Single Phase to Earth Fault Current Compensation in Networks with Arc Suppression Coil in Neutral Point 5

Development of a Method of Automatic Single Phase to Earth F...

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5th International Youth Scientific and Technical Conference Relay Protection and Automation, RPA 2022

作者： Kutumov, Yu. D. Shadrikova, T.Yu. Shuin, V.A. Ivanovo State Power Engineering University Jsc so Ups Branch of Ido Center Automatic Control of Electrical Power Systems Department Ivanovo Russia

ISBN: (数字)9798350399912

ISBN: (纸本)9798350399912

At the present time approximately 20% of 6-10 kV cable networks operate with resonant-grounded via arc-suppression coil (ASC) neutral point [1]. Meanwhile, an increasing number of experts note that resonant grounding of neutral point via ASC cannot solve the issue of single phase to earth faults (SPEF) negative consequences and their most dangerous variation, which is called intermittent arc single phase to earth fault (IASPEF) [for example, 2]. The main reasons for the inadequate efficiency of this neutral grounding mode are higher harmonic components in steady-state SPEF current, as well as higher harmonic components which are due to intensive transient processes during SPEF, which cannot be compensates by the usage of ASC. For the compensation of these components it is necessary to apply the devices, which will be complement ASC;these devices, together with the ASC, can be called a system of full compensation of the SPEF current. © 2022 IEEE.

关键词： Electric grounding

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Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling Under Data Governance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 351-361页

作者： Qin, Zhaoming Dong, Nanqing Liu, Di Wang, Zhefan Cao, Junwei EPFL Automatic Control Laboratory Lausanne1015 Switzerland Shanghai Artificial Intelligence Laboratory Shanghai200232 China Tsinghua University Department of Electrical Engineering Beijing100084 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

As a data-driven approach, multi-agent reinforcement learning (MARL) has made remarkable advances in solving cooperative residential load scheduling problems. However, centralized training, the most common paradigm for MARL, limits large-scale deployment in communication-constrained cloud-edge environments. As a remedy, distributed training shows unparalleled advantages in real-world applications but still faces challenge with system scalability, e.g., the high cost of communication overhead during coordinating individual agents, and needs to comply with data governance in terms of privacy. In this work, we propose a novel MARL solution to address these two practical issues. Our proposed approach is based on actor-critic methods, where the global critic is a learned function of individual critics computed solely based on local observations of households. This scheme preserves household privacy completely and significantly reduces communication cost. Simulation experiments demonstrate that the proposed framework achieves comparable performance to the state-of-the-art actor-critic framework without data governance and communication constraints. © 2023 IEEE.

关键词： Reinforcement learning

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Simulation of Conducted Emissions From Power Converters Using Leading Switching Technologies 7

Simulation of Conducted Emissions From Power Converters Usin...

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7th IEEE Global Electromagnetic Compatibility Conference, GEMCCON 2023

作者： Madi, Amr Vieira, Francinei Lezynski, Piotr Koj, Sebastian Smolenski, Robert Enschede Netherlands Institute of Electrical Engineering and Measurement Technology Leibniz University Hannover Hannover Germany Institute of Automatic Control Electronics and Electrical Engineering University of Zielona Gora Zielona Gora Poland Jade University of Applied Sciences Department of Engineering Sciences Wilhelmshaven Germany

ISBN: (纸本)9798350396935

This paper presents a comparative study between the commonly used switches (IGBT, MOSFET, SiC and GaN) for power inverters of electric vehicles. A 400 V, three-phase inverter system simulation test is implemented using LTspice and the conducted emissions are compared to variant CISPR standards and switching frequencies in order to show the possible interferences with the other car equipment. © 2023 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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System Optimal Routing and Distribution of Benefits on National Road Networks

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Transportation Research Procedia 2025年 82卷 2532-2545页

作者： Alexander Roocroft Giuliano Punzo Muhamad Azfar Ramli Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Institute of High Performance Computing A*STAR Singapore

Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rerouting through the empirical price of anarchy, a measure of network efficiency. However, studies using real-world measurements have been limited by methodological accuracy and network size. Also, they have lacked understanding of the spatial distribution of benefits from rerouting and the relationship with marginal external cost road charges that can be used for implementation. In this article, we create an accurate data-driven traffic assignment model of England's Strategic Road Network. We use it to calculate the national price of anarchy, which is found to be almost 1 implying gains from rerouting at the national scale are minimal and smaller than in other studies. The results show the distribution of rerouting benefits varies strongly with different network zones and demand profiles. This did not match the distribution of marginal external cost charges. Some zones have noticeable benefits from rerouting although the overall network benefit is small, however, these zones do not coincide with where the largest road charges have to be applied for system-optimal rerouting. These results have implications for rerouting implementation.

关键词： Strategic Road Network Empirical Price of Anarchy National Traffic Assignment

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