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Energy, Power and Electrical engineering (EPEE), International Conference on

作者： Jinpeng Kan Yongqing Meng Changyi Li Wenjie Chen Fengjiao Li Yixin Shi School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

Power electronic switching devices and pulse width modulation (PWM) not only improves the performance of motor drive systems, but also brings about common-mode voltage (CMV) issues, that challenging the normal operation of the system. This article proposes a zero common-mode voltage modulation strategy based on unified voltage modulation for a 60° Y-connected six-phase permanent magnet synchronous motor system driven by a dual three-phase inverter. The theoretical basis and zero common-mode implementation scheme of unified modulation are analyzed, and the effectiveness of the proposed zero common-mode voltage modulation strategy is finally verified through simulation.

关键词： Pulse width modulation inverters Performance evaluation Simulation Modulation Voltage Switches Permanent magnet motors Inverters Permanent magnets Switching circuits

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MealWatcher: A New Toolset to Record Meals for the Development of Automated Energy Intake Estimation

MealWatcher: A New Toolset to Record Meals for the Developme...

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2024 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2024

作者： Armin, Faria Jolly, James Nguyen, James Rangaraju, Lakshmi Regan, Daniel Brown, Zoe O'Toole, Sharon Raynor, Hollie Brick, Leslie Jelalian, Elissa Thomas, J. Graham Goldstein, Stephanie P. Hoover, Adam Clemson University Department of Electrical and Computer Engineering ClemsonSC29631 United States Weight Control and Diabetes Research Center The Miriam Hospital ProvidenceRI02916 United States University of Tennessee Department of Nutrition KnoxvilleTN37996 United States Alpert Medical School Brown University Department of Psychiatry and Human Behavior ProvidenceRI02903 United States Weight Control and Diabetes Research Center The Miriam Hospital/Brown Alpert Medical School Department of Psychiatry and Human Behavior ProvidenceRI02916 United States

ISBN: (纸本)9798350351552

Classic tools for measuring energy intake, such as food diaries and 24 hour recalls, are burdensome to use and have significant measurement error. This hinders research and interventions in obesity treatment and comorbidities such as diabetes and heart disease. New tools are being developed to automate the measurement of energy intake, such as wearable devices like smartwatches. Towards this goal, several datasets have been collected and made publicly available that include hand motion. However, these datasets have been limited to the wrist part of hand motion, and have only been collected in controlled environments such as labs or cafeterias. In this work we describe a new toolset that supports data collection from a smartwatch and smart ring simultaneously, to be used in home, cafeteria, and free-living environments, with real-time user feedback to assist with energy intake estimation. This data collection is ongoing and will eventually encompass 600 subjects. This paper describes the toolset and preliminary results for 16 subjects, including a comparison of smart ring versus smartwatch intake gesture detection. The smart ring achieved an F1 score of 0.74 compared to an F1 score of 0.8 from the smartwatch. Finally, we describe the full set of experiments we intend to perform with the complete dataset. © 2024 IEEE.

关键词： Gesture recognition

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Q-Learning Based control for Swing-Up and Balancing of Inverted Pendulum

Q-Learning Based Control for Swing-Up and Balancing of Inver...

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Intermountain engineering, Technology and Computing (IETC)

作者： Antora Dev Kanan Roy Chowdhury Marco P. Schoen Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Measurement & Control Engineering Research Center (MCERC) Idaho State University Pocatello ID USA

ISBN: (数字)9798350373073

ISBN: (纸本)9798350373080

This study addresses the classic control problem of stabilizing an inverted pendulum on a moving cart, a challenge in control theory and robotics due to its inherent instability and highly nonlinear dynamics. We explore the application of Q-learning, a model-free reinforcement learning algorithm, and its efficacy in deriving an optimal control policy for the system without precise system models. Our approach utilizes Q-learning's capacity for stabilizing a pendulum in an upright position on the top of the horizontally moving cart within a certain boundary. Our strategy adapts to a dynamic environment while showcasing its robustness in developing control policies for complex systems. This research bridges classical control theory with reinforcement learning techniques, contributing to the domain by demonstrating the versatility and potential of machine learning in control tasks.

关键词： Adaptation models Q-learning Heuristic algorithms Optimal control Robustness control theory Nonlinear dynamical systems

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Recent advances in AI for enhanced environmental monitoring and preservation

Recent advances in AI for enhanced environmental monitoring ...

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IEEE International Workshop on Metrology for the Sea;Learning to Measure Sea Health Parameters (MetroSea)

作者： Paolo Russo Fabiana Di Ciaccio Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Rome Italy Department of Civil and Environmental Engineering University of Florence Florence Italy

This paper explores the potential applications of cutting-edge Artificial Intelligence (AI) technologies, specifically Vision Transformer and Diffusion models in the field of environmental monitoring and preservation. By analyzing the current state of the art, we highlight the potential of these advanced techniques in capturing, analyzing, and communicating environmental data. Vision Transformer models demonstrate their effectiveness in identifying and classifying environmental features, while Diffusion models offer realistic image generation capabilities. We discuss the diverse applications of these models, such as visualizing environmental impacts, enhancing data quality, and generating synthetic images for training datasets. By bridging the gap between AI advancements and environmental research, this paper paves the way for improved accuracy, efficiency, and communication in the realm of sustainable environmental practices.

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Cardiac Ischemia Detection Using Self-Organizing Map Feature Selection Method

Cardiac Ischemia Detection Using Self-Organizing Map Feature...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Ramin Aghili Karampour Amir Arshia Bakhtiar Kiarash Hajizamani Alireza Fallahi Hamid Soltanian Zadeh Biomedical Engineering Department Hamedan University of Technology Hamedan Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (数字)9798331529710

ISBN: (纸本)9798331529727

Cardiac ischemia, a prevalent cause of heart failure, remains the leading cause of death in Iran. Early diagnosis of this condition is crucial, and electrocardiogram (ECG) signal processing techniques offer valuable insights. By analyzing ECG signals from ischemic patients and comparing them to those of normal individuals, we can extract relevant features for classification. Our study extracted some features from ECG signals, including statistical, time-based, frequency, and time-frequency features. We employed the self-organizing maps method (SOM) to identify the most informative features. Subsequently, we evaluated the classification accuracy using several machine learning algorithms, including support vector machines (SVM), Naive Bayes, Linear Discriminant Analysis (LDA), and Logistic Regression. The results demonstrated the superiority of the SOM method in selecting the best features compared to PCA, with accuracies of $\mathbf{9 1. 2 \%}, \mathbf{8 4. 3 \%}, \mathbf{7 2. 5 \%}$, and $88.9 \%$ for SVM, LDA, NB, and LR methods, respectively. Our findings contribute to the early detection and management of cardiac ischemia, potentially improving patient outcomes.

关键词： Self-organizing feature maps Support vector machines Time-frequency analysis Logistic regression Accuracy Machine learning algorithms Electrocardiography Signal processing Feature extraction Principal component analysis

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Computationally Efficient Implementation of the Weighted Kalman Filter for Quadratic Systems

Computationally Efficient Implementation of the Weighted Kal...

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American control Conference (ACC)

作者： Damiano Rotondo Marcin Witczak Lothar Seybold Department of Electrical and Computer Engineering (IDE) University of Stavanger Norway Institute of Control and Computation Engineering University of Zielona Gora Poland RAFI GmbH & Co. KG Germany

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

The weighted Kalman filter (WKF) can be per- ceived as a variant of the extended Kalman filter (EKF), which incorporates the so-called weighted linearisation. The price behind such an extension is expressed by an increased computational complexity, which aims at improving the overall convergence of the filter. Owing to the increased complexity, the WKF is in general not suitable for high-order nonlinear systems. To overcome this difficulty, the objective of this paper is to show that a closed-form expression of the WKF can be obtained for a specific class of nonlinear systems, i.e., those characterised by a quadratic state equation. This closed-form of the WKF scales well with the order of the system, enabling the application of the WKF to high-order nonlinear quadratic systems, as exemplified in the final part of the paper using a comprehensive Monte Carlo analysis applied to a large number of random systems.

关键词： Closed-form solutions Monte Carlo methods Simulation Integral equations control systems Mathematical models Computational efficiency

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Fractional Order Sliding Mode control with Fuzzy Parameter Tuning Applied to a SCARA Robot

Fractional Order Sliding Mode Control with Fuzzy Parameter T...

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Mechatronic Systems Supervision (IW_MSS), IEEE International Workshop on

作者： Aicha Znidi Fatma Abdelhedi Ahmed Said Nouri Nabil Derbel Lab: Numerical Control of Industrial Processes National Engineering School of Gabes University of Gabes Tunisia Department of Electrical and Computer Engineering College of Engineering King Abdulaziz University Jeddah Saudi Arabia Control & Energy Management Laboratory University of Sfax National Engineering School of Sfax Tunisia

ISBN: (数字)9798350378382

ISBN: (纸本)9798350378399

This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both advantages of fractional calculus and sliding mode control to upgrade the robustness and the performances of the controller. Moreover, the paper proposes to use a fuzzy tuning of sliding mode controller in order to satisfy the capabilities of the actuators. The stability of the closed loop system has been demonstrated using the Lyapunov theory. Simulation results demonstrate the efficiency of the proposed method achieving precise trajectory tracking and robust performances, it has been shown that fuzzy tuning of the sliding function parameters significantly reduces control variable peaks, making the control more suitable for actuator application.

关键词： Asymptotic stability Actuators Trajectory tracking Simulation Manipulators Stability analysis Closed loop systems Tuning Sliding mode control Fractional calculus

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Estimating the job's pending time on a high-performance computing cluster through a hierarchical data-driven methodology 23

Estimating the job's pending time on a high-performance comp...

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23rd International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, DOLAP 2021

作者： Carfí, Fabio Capitelli, Enrica Nosenzo, Vladi Massimo Cerquitelli, Tania Department of Control and Computer Engineering Politecnico di Torino Turin Italy CNH Industrial Turin Italy

Nowadays, manufacturing industries have to shorten the time to market to satisfy customers' needs and survive in globally competitive contexts. For these reasons, all the steps required to create new products need to be optimized as much as possible to minimize the overall execution time. Technologies like CAD (computer-Aided Design) and CAE (computer-Aided engineering) are useful in this process. At the same time, Finite Element Methods are fundamental because they allow performing simulations, not only of mechanical components but also of an entire manufacturing process. Doing so, there is the possibility to avoid errors which would entail the need to carry out further operations and, therefore, increase execution time during the product's creation. In the context of heavy simulations performed on High-Performance Computing (HPC) architectures, it is challenging to estimate each job's pending time, i.e., the time between the job submission and the job execution starting time. This information could support the optimization of the resource requests, drastically reducing the waiting times needed to obtain the simulations' results. This paper presents an innovative and hierarchical data-driven methodology to estimate the discretized value of pending time, i.e., estimating the range time that a job will have to wait before the necessary hardware resources are supplied for its execution. A large set of experiments have been performed on a real dataset collected in an Italian industrial context to assess the proposed approach's effectiveness in correctly and accurately predict the pending time's discretized value. This work is a preliminary step towards implementing a scheduling system based on machine learning techniques. © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： computer aided engineering

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Exploiting Hankel–Toeplitz Structures for Fast Computation of Kernel Precision Matrices

arXiv

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arXiv 2024年

作者： Viset, Frida Kullberg, Anton Wesel, Frederiek Solin, Arno Delft Center for Systems and Control Delft University of Technology Netherlands Department of Electrical Engineering Linköping University Sweden Department of Computer Science Aalto University Finland

The Hilbert–space Gaussian Process (hgp) approach offers a hyperparameter-independent basis function approximation for speeding up Gaussian Process (gp) inference by projecting the gp onto M basis functions. These properties result in a favorable data-independent O(M3) computational complexity during hyperparameter optimization but require a dominating one-time precomputation of the precision matrix costing O(NM2) operations. In this paper, we lower this dominating computational complexity to O(NM) with no additional approximations. We can do this because we realize that the precision matrix can be split into a sum of Hankel–Toeplitz matrices, each having O(M) unique entries. Based on this realization we propose computing only these unique entries at O(NM) costs. Further, we develop two theorems that prescribe sufficient conditions for the complexity reduction to hold generally for a wide range of other approximate gp models, such as the Variational Fourier Feature (vff) approach. The two theorems do this with no assumptions on the data and no additional approximations of the gp models themselves. Thus, our contribution provides a pure speed-up of several existing, widely used, gp approximations, without further approximations. © 2024, CC BY.

关键词： Gaussian distribution

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An α-regret analysis of adversarial bilateral trade

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Artificial Intelligence 2024年 337卷

作者： Azar, Yossi Fiat, Amos Fusco, Federico Tel Aviv University Tel Aviv Israel Sapienza University of Rome Department of Computer Control and Management Engineering "Antonio Ruberti" Via Ariosto 25 Rome00185 Italy

We study sequential bilateral trade where sellers and buyers valuations are completely arbitrary (i.e., determined by an adversary). Sellers and buyers are strategic agents with private valuations for the good and the goal is to design a mechanism that maximizes efficiency (or gain from trade) while being incentive compatible, individually rational and budget balanced. In this paper we consider gain from trade, which is harder to approximate than social welfare. We consider a variety of feedback scenarios and distinguish the cases where the mechanism posts one price and when it can post different prices for buyer and seller. We show several surprising results about the separation between the different scenarios. In particular we show that (a) it is impossible to achieve sublinear α-regret for any α © 2024 The Author(s)

关键词： Adversarial machine learning

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