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23rd International Middle East Power Systems Conference, MEPCON 2022

作者： Tazy, Ahmed Samy, Mohamed Mahmoud Ghalib, Mohamed Ali Albaha University Faculty of Engineering Electrical Engineering Department KSAt Saudi Arabia University of Beni-Suef Dept. of Electrical Engineering Beni-Suef Egypt College of Technology and Education Beni-Suef University Dept. of Process Control Beni-Suef Egypt

ISBN: (纸本)9781665463638

controlling frequency and voltage stability is the major objective of controlling an independent mode a difficult task since every distributed power supply Distributed energy resource (DERs). A small network can include various converters, connected in parallel to each other by lines with mismatched line resistance. The micro-grid includes both local and general loads. The conventional droop controller shows poor reactive power sharing when mismatched line impedance among DER modules is unable to ensure the stability of the microgrid, also, the reactive power sharing accuracy among inverters is not made accurate. In this study, an improved control strategy using a secondary central small network unit (SCMU), to increase the precision of power-sharing, also provides the most dynamic damping of the oscillator system. To improve the accuracy of power sharing and to improve the voltage on the bus at load, this controller is combined with sliding mode control. Two inverters connected in parallel were used to perform the simulation and the control model. The results showed the effectiveness of the proposed technique on the conventional control. © 2022 IEEE.

关键词： controllers

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Chaos in pulsar spin dynamics

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IFAC-PapersOnLine 2023年第1期56卷 199-203页

作者： Berc Deruni Mustafa Dogan Department of Engineering Yeditepe University Istanbul 34755 Turkey Department of Control and Automation Engineering Faculty of Electrical-Electronics Engineering Istanbul Technical University Istanbul 34469 Turkey

In the present paper, a new model describing neutron star dynamics is analysed. The system under consideration can be described as a modified vortex creep model. Two component model and the vortex creep model have been used successfully to describe post glitch relaxation phase. However, glitch behaviour is yet to be explained. There can be a possible stochastic mechanism that trigger glitches in neutron stars. To this aim, we propose a modification in the nonlinear vortex creep model. The significance of the modification is twofold, the dynamics of the system is able to generate intermittency, imitating the glitch behaviour of pulsars, and the system also show chaotic motion when the system parameters are set accordingly. The chaotic dynamics is verified by using nonlinear tools such as numerical phase portraits, Lyapunov exponents and bifurcation diagrams.

关键词： Pulsar spin dynamics nonlinear superfluidity chaos intermittency

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Multi-Objective Optimization of Individual Pitch control for Blade Fatigue Load Reductions for a 15 MW Wind Turbine

Multi-Objective Optimization of Individual Pitch Control for...

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European control Conference (ECC)

作者： Manuel Lara Francisco Vázquez Jan-Willem van Wingerden Sebastiaan Paul Mulders Juan Garrido Department of Electrical Engineering and Automation University of Cordoba Cordoba Spain Delft Center for Systems and Control Faculty of Mechanical Engineering Delft University of Technology Delft The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In order to mitigate periodic blade loads in wind turbines, recent research has analyzed different Individual Pitch control (IPC) approaches, which typically use the multi-blade coordinate (MBC) transformation. Some of these studies show that the introduction of an additional tuning parameter in the MBC, namely the azimuth offset, helps to decouple the nonrotating axes in the MBC transformation and enhances the IPC performance. However, these improvements have been studied without considering the increased control effort performed by the pitch signal, which is the main negative side effect of the IPC. This work addresses this trade-off between pitch signal effort and blade fatigue reduction for IPC applied to a wind turbine operating in the full load region. Here, two IPC schemes, with and without additional azimuth offset, are designed and applied to a 15 MW monopile offshore wind turbine simulated with OpenFAST software. The optimal tuning of the IPC parameters is performed by means of a multi-objective optimization solved by genetic algorithms. The optimization procedure minimizes two objective functions related to pitch signal effort and blade fatigue load. The resulting Pareto fronts show a range of optimal solutions for each IPC scheme. The selected optimal solution for IPC with azimuth offset compared to the optimal solution for IPC without offset achieves improvements of more than 10% in blade load reduction maintaining similar pitch signal effort.

关键词： Azimuth Blades Simulation Fatigue Linear programming Software Wind turbines

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Tracking performance limitations of MIMO discrete-time networked control systems with multiple constraints

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Science China(Information Sciences) 2023年第8期66卷 267-268页

作者： Xiaowei JIANG Bin ZHANG Xiangyong CHEN Huaicheng YAN School of Automation China University of Geosciences Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation and Electrical Engineering Linyi University Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education

Dear editor,Networked control systems(NCSs) have attracted widespread attention in some fields because they offer the advantages of reduced cabling, greater resource sharing,and ease of installation and maintenance [1]. However, in an unreliable network environment, network constraints can significantly limit the performance of NCSs.

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Linear parameter-varying model predictive control for nonlinear systems using general polytopic tubes

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Automatica 2024年 160卷

作者： Abbas, Hossam Seddik Institute for Electrical Engineering in Medicine University of Lübeck Moislinger Allee 53-55 Lübeck23558 Germany Automation and Control Group Department of Electrical and Information Engineering Faculty of Engineering Kiel University Kaiserstraße 2 Kiel24143 Germany

This paper deals with model predictive control (MPC) for nonlinear systems using linear-parameter varying (LPV) embedding of the nonlinear dynamics (LPVMPC). The proposed LPVMPC can incorporate information of the future evolution of the scheduling parameter over the MPC prediction horizon with uncertainty bounds, which are used to construct anticipated scheduling tubes for robustification. Therefore, this approach is less conservative than the methods that only consider knowledge of the bounds on the scheduling parameter's rate of variation. The scheduling tubes are employed to synthesize online general polytopic invariant state tubes. The optimization problem of the proposed LPVMPC is a single quadratic program. Recursive feasibility is proven. A numerical example is presented for demonstrating the effectiveness of the proposed LPVMPC algorithm compared to nonlinear MPC and other standard approaches. © 2023 Elsevier Ltd

关键词： Model predictive control

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An Enhanced Finite-Set Model Predictive control Based Super Twisting Sliding Mode Speed controller for Linear Metro Applications 24

An Enhanced Finite-Set Model Predictive Control Based Super ...

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24th International Middle East Power System Conference, MEPCON 2023

作者： Ali, Mosaad M. Elmorshedy, Mahmoud F. Gabr, Mohamed A. Ramadan, Haitham S. Lotfy, Mostafa Wageh Kafrelsheikh University Faculty of Engineering Department of Electrical Engineering Egypt Tanta University Faculty of Engineering Department of Electric Power and Machines Engineering Tanta31733 Egypt Prince Sultan University Renewable Energy Laboratory College of Engineering Riyadh11586 Saudi Arabia Zagazig University Faculty of Engineering Electrical Power and Machines Dept. Zagazig44519 Egypt Institut International sur le Stockage de l'Hydrogène Isthy Belfort Territory Meroux-Moval90400 France Beni-Suef University Faculty of Technology and Education Department of Process Control Technology Beni Suef Egypt

ISBN: (纸本)9798350358469

The tracking speed issue of linear induction machines (LIMs) is addressed in this study via a nonlinear speed controller with model predictive current control (MPCC). The super twisting sliding mode controller (STSMC) controls the LIM speed instead of the traditional PI controller to provide a quick dynamic response with a smaller steady-state inaccuracy. The primary objective of the super twisting sliding mode controller (STSMC) is to regulate the q-axis primary current within the finite-set MPCC (FS-MPCC) framework. To avoid the use of an axis transformation problem and speed up the calculation process, the dynamic model of the suggested STSMC-based FSMPCC is fulfilled in the α β frame rather than the dq frame. The suggested control technique is validated by simulation results based on the platform of two 3 kW arc induction motor drive systems. © 2023 IEEE.

关键词： Model predictive control

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

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

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Mediterranean Conference on control and automation (MED)

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

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

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.

关键词： Ultrasonic imaging Transforms Feature extraction Time measurement Fractals Ensemble learning Image preprocessing

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Robust control for a Class of Nonlinear Systems Against Denial-of-Service Attacks

Robust Control for a Class of Nonlinear Systems Against Deni...

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2021 China automation Congress, CAC 2021

作者： Ding, Wei Zhang, Jin-Xi Faculty of Electrical Engineering and Automation Changshu Institute of Technology Changshu China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (纸本)9781665426473

This paper explores the state-feedback control problem for a family of nonlinear systems subject to denial-of-service (DoS) attacks. The unknown nonlinearities and DoS attacks involved in the closed loop render the existing approaches for resilient control of linear systems or robust nonlinear control infeasible. A solution is provided by designing a novel robust control scheme together with a constraint-handling technique. Two technical lemmas are also given to establish the boundedness of the signals in the resulting control system. As a distinct property, our approach is flexible enough such that the system reaches a predefined steady state in a specified time after the occurrence of DoS attacks. © 2021 IEEE

关键词： Denial-of-service attack

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Deep Transfer Learning-Based Intelligent Diagnosis of Malignant Tumors on Mammography 3

Deep Transfer Learning-Based Intelligent Diagnosis of Malign...

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3rd International Conference on Industrial Artificial Intelligence, IAI 2021

作者： Ding, Wei Zhang, Jin-Xi Changshu Institute of Technology Faculty of Electrical Engineering and Automation Changshu China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang China

ISBN: (纸本)9781665435178

In this paper, we propose a deep transfer learning-based intelligent diagnosis approach for malignant tumors on mammography. An image segmentation algorithm is developed to remove the background, noise, and other redundancy in the image, for improving the learning efficiency. Based on the GoogleNet after training, we apply the transfer learning technique to the processed image. In this way, the accuracy of the classification model is improved. The experiment results show that the accuracy of our image segmentation algorithm is 100%, using only one-third of the data in training;the accuracy of our training approach is with the highest and average accuracy of 83% and 70%, respectively, by 2 × 104 iterations;and the area under the receiver operating characteristic curve is 0.77. These results are superior to those obtained by the existing methods. © 2021 IEEE.

关键词： Image enhancement

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Triple Parallel LSTM Networks for Classifying the Gait Disorders Using Kinect Camera and Robot Platform During the Clinical Examination

Triple Parallel LSTM Networks for Classifying the Gait Disor...

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electrical, Computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Mohsen Shayestegan Tomas Zalabsky Jan Mareš Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic Faculty of Electrical Engineering and Informatics Research Center University of Pardubice Pardubice Czech Republic Department of Process Control Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic

This paper presents a new methodology for the data processing and classification method for gait disorders, which is observed with a Kinect camera. The study of gait and motion stability in gait disorders is one of the most interesting research areas in the field. The patient and the physician must monitor the progress of the rehabilitation process before and after surgery to obtain an objective view of the rehabilitation process. In this study, the patient is scanned with the Kinect camera placed on a mobile robotic platform. For feature extraction and feature analysis, the exercises (three walking exercises) frames are collected and saved in data folders. This study uses 84 measurements of 37 patients with complex observations based on the physician's opinion in a clinical setting to address classification problems. In the analysis of gait disorders, motion data play an essential role. Furthermore, it reduces the selection of helpful body features for assessing gait disorders. The proposed system uses a key-point detector that computes body landmarks and classifies gait disorders using triple-parallel long short-term memory (LSTM) networks. The present study demonstrates the success of the method in classification evaluation when combined with the state-of-the-art pose estimation method. Around 81 percent accuracy was achieved for given sets of individuals using velocity-based, angle-based, and position-based features.

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