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2021 International MultiConference of Engineers and Computer Scientists, IMECS 2021

作者： Takezaki, Shumpei Kishida, Kazuya The Advanced Mechanical and Electronic Control Systems Engineering National Institute of Technology Kagoshima College 1460-1 Shinko Hayato Kirishima Kagoshima899-5102 Japan The Department of Electronic Control Engineering National Institute of Technology Kagoshima College Japan

ISBN: (纸本)9789881404916

Cardiovascular diseases (CVDs) are the main cause of deaths all over the world. To detect the abnormalities of a heart automatically, convolutional neural networks (CNNs) learned by using heart sound signals (i.e., the phonocardiogram or PCG) are proposed. Generally, CNNs need sufficient annotated training data to achieve the high performance. However, the annotated PCGs (i.e. PCGs labelled with abnormal or normal) dataset is not sufficient because of personal information and burden of physicians. Therefore, we need to improve the classification performance of CNNs even when annotated PCGs is insufficient. In this paper, in order to solve above problem we consider two data augmentation (DA) methods, one is Window Slicing with Spectrogram (WSS), which slices single PCG to make multiple signals and transforms the signals into spectrogram data, the other is Synthetic Spectrogram based GANs (SSG), which generates synthetic data using generative adversarial networks (GANs). In order to show the validity of considered two DA methods, we perform some experiments concerning heart sounds detection and discuss the results of experiments in point of the accuracy, the sensitivity and the specificity. © 2021 Newswood Limited. All rights reserved.

关键词： Convolutional neural networks Data augmentation Generative adversarial networks Heart sound detection

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Learning-based control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy 49

Learning-based Control for PMSM Using Distributed Gaussian P...

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49th Annual Conference of the IEEE Industrial electronics Society, IECON 2023

作者： Yin, Zhenxiao Dai, Xiaobing Yang, Zewen Shen, Yang Hattab, Georges Zhao, Hang Robotics and Autonomous Systems Thrust Guangzhou China Technical University of Munich Chair of Information-oriented Control Munich Germany Berlin Germany Freie Universität Berlin Department of Mathematics and Computer Science Berlin Germany The Hong Kong University of Science and Technology Department of Electronic & Computer Engineering Hong Kong

ISBN: (纸本)9798350331820

The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs). To infer the unknown part of the system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility of continuous system modeling and its guaranteed performance. For practical implementation, distributed GPR is adopted to alleviate the high computational complexity. However, the study of distributed GPR from a control perspective remains an open problem. In this paper, a control-aware optimal aggregation strategy of distributed GPR for PMSMs is proposed based on the Lyapunov stability theory. This strategy exclusively leverages the posterior mean, thereby obviating the need for computationally intensive calculations associated with posterior variance in alternative approaches. Moreover, the straightforward calculation process of our proposed strategy lends itself to seamless implementation in high-frequency PMSM control. The effectiveness of the proposed strategy is demonstrated in the simulations. © 2023 IEEE.

关键词： Synchronous motors

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Non-Convex Potential Games for Finding Global Solutions to Sensor Network Localization

Non-Convex Potential Games for Finding Global Solutions to S...

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European control Conference (ECC)

作者： Gehui Xu Guanpu Chen Yiguang Hong Baris Fidan Thomas Parisini Karl H. Johansson Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results.

关键词： Location awareness Coordinate measuring machines Simulation Current measurement Noise Europe Games

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

A Multi-Player Potential Game Approach for Sensor Network Lo...

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IEEE Conference on Decision and control

作者： Gehui Xu Guanpu Chen Baris Fidan Yiguang Hong Hongsheng Qi Thomas Parisini Karl H. Johansson Department of Electrical and Electronic Engineering Imperial College London London UK Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Control Science and Engineering Tongji University shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies.

关键词： Location awareness Noise Games Position measurement Nash equilibrium Distance measurement Noise measurement

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A Predictive control based Scheme for Maximum Power Extraction of PMSG based Wind Turbine systems

A Predictive Control based Scheme for Maximum Power Extracti...

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IEEE International Symposium on Industrial electronics (ISIE)

作者： Fahimeh Shiravani Jose Antonio Cortajarena Patxi Alkorta Mikel Gonzalez Perez Oscar Barambones Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa – EIG/Eibar Basque Country University Spain Department of Electronic Technology School of Engineering of Gipuzko– EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa-EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Vitoria Basque Country University Spain

In this proposal, a predictive control scheme is considered for PMSG based wind turbine system in order to maximize power extraction. The main goal is to maintain the turbine tip-speed ratio (and consequently the power coefficient) at its optimal point and regulate the PMSG rotor speed in reaction to the variation of wind speed. The control of generator speed is done by employing a generalized predictive controller. This regulator by taking advantage of the predictive feature can prepare the generator to react to the upcoming wind in advance and consequently increases the efficiency of the turbine. Also, it has been demonstrated that this controller enhances the transient response of the system compared to the conventional methods. The proposed controller has been validated through Matlab/Simulink and an experimental test bench.

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Fast and Robust Energy Router control in Dynamic Conditions Using Flatness-Based control Theory

Fast and Robust Energy Router Control in Dynamic Conditions ...

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Compatibility in Power electronics (CPE)

作者： Mohammadreza Azizi Oleksandr Husev Carlos Roncero-Clemente Oleksandr Veligorskyi Ryszard Strzelecki Department of Radiotechnic and Embedded Systems Chernihiv Polytechnic National University Chernihiv Ukraine Department of Electric Electronic and Automation Engineering University of Extremadura Badajoz Spain Faculty of Electrical and Control Engineering Gdansk University of Technology Gdansk Poland

ISBN: (数字)9798331515171

ISBN: (纸本)9798331515188

In this paper, flatness-based control theory is developed to enhance the dynamic performance of a multiport energy router. The energy router integrates multiple power sources and sinks, including photovoltaic systems, battery storage, the grid, and various loads. Consequently, any sudden change in a subsystem can induce dynamic conditions across the entire system. The presented method controls the grid-side inverter and regulates the de link voltage. To implement this control approach, the system equations have been established, and it has been demonstrated that the system is differentially flat. Afterward, the controller design has been addressed. The simulation results confirm the proper performance of this method, and the comparisons made validate the high speed and accuracy of the system responses compared to conventional solutions.

关键词： Photovoltaic systems Power engineering Accuracy Simulation Modulation control systems Inverters Mathematical models control theory Voltage control

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A Parkinson's Bradykinesia Recognition System Based on Deep Learning Method 12

A Parkinson's Bradykinesia Recognition System Based on Deep ...

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12th International Conference on CYBER technology in Automation, control, and Intelligent systems, CYBER 2022

作者： Tong, Lina Liu, Daisong Zhang, Mingjia Peng, Liang Department of State Key Laboratory of Management and Control for Complex Systems Institute of Automation China Academy of Science Beijing China School of Mechanical Electronic and Information Engineering Chinese University of Mining and Technology-Beijing Beijing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Parkinson's disease is a neurodegenerative disease common in middle-aged and elderly people, and bradykinesia is one of the most obvious symptoms. In this study, A deep learning-based Parkinson's bradykinesia recognition system is designed which has an inertial sensor-based data acquisition system. It can wirelessly collect bradykinesia kinematic information by wearing it on the wrist and ankle of Parkinson's patients. In addition, a method for identifying the symptom of Parkinson's bradykinesia based on Long Short Term Memory (LSTM) Network is proposed, with an accuracy of 98.6%. It provides a feasible method to identify Parkinson bradykinesia to assist the diagnosis and treatment. © 2022 IEEE.

关键词： Neurodegenerative diseases

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt 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 Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Iterative Learning Based Train Stop control with Initial State Shifts for Urban Rail Transit 10

Iterative Learning Based Train Stop Control with Initial Sta...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Yu, Ruochuan Tang, Tao Yin, Chenkun Xun, Jing Xi, Jiayi Zheng, Xiaobin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Advanced Control Systems Laboratory School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Traffic Control Technology Co. Ltd Beijing100070 China Beijing Transport Institute Beijing100073 China

ISBN: (纸本)9781665424233

In this paper, a partitioned terminal iterative learning control (TILC) strategy for urban rail transit with initial state shifts is proposed to solve the accurate stop problem. A supervised machine learning method is used to pre-processing the historical operation data (i.e. the initial speed and the position data pairs in the stopping stage). And for each category the TILC algorithm is applied, realizing the update of the control law in a small range. Simulation results show that the proposed algorithm can achieve the stop accuracy of ±15cm even though the initial state varies over a certain range during the iterations. This meets the general requirement of accurate train stop for urban rail transit (±30cm). © 2021 IEEE.

关键词： Iterative methods

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Scheduling of over-actuated networked control systems

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IFAC-PapersOnLine 2022年第13期55卷 25-30页

作者： J. Kreiss R. Postoyan D. Nešić W.P.M.H. Heemels Université de Lorraine CNRS CRAN F-54000 Nancy France Department of Electrical and Electronic Engineering University of Melbourne Parkville VIC 3010 Australia Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We investigate the scenario where an over-actuated plant is controlled over a network. We concentrate on the effect of two network-induced phenomena: varying transmission intervals and scheduling, in the sense that only one of the actuators receives new data at each transmission instant. We present an emulation-based solution for the controller design, i.e., the controller is first designed to stabilize the origin of the plant ignoring the network and second, the packet-based network is taken into account and conditions on the maximum allowable transmission interval (MATI) and the scheduling protocol are given to preserve the stability of the closed-loop system. Our results are tailored to over-actuated plants leading to significant improvements compared to applying off-the-shelf results available in the literature. In particular, a new model is derived and new conditions on the scheduling protocol are given, which lead to a two-measure stability property for the networked control system. We illustrate how new classes of scheduling protocols can be derived by exploiting over-actuation, which leads to larger MATI bounds compared to applying existing results, as shown on a numerical example.

关键词： Networked control systems over-actuated systems hybrid systems stability of hybrid systems Lyapunov methods

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