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检索条件"机构=Dept. of Control and Computer Engineering - DAUIN"

共 1085 条记录，以下是131-140 订阅

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Lightweight Direct Memory Access on FPGA Using AXI Protocol

Lightweight Direct Memory Access on FPGA Using AXI Protocol

引用

computer Science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Adam Kidwell Matthew P. Horvath Darrin Hanna Bryant Jones Dept. of Electrical and Computer Engineering Oakland University Rochester Hills MI Intrepid Control Systems Troy MI

This paper presents a lightweight AXI DMA controller architecture useful for embedded systems that do not require fully featured DMA controllers. Simulation is accomplished with VUnit, and implementation results are obtained on a Xilinx XC7Z010CLG400-1 FPGA. When compared with Xilinx's AXI DMA controller with the same configuration, the presented controller utilizes between 16 and 82% fewer resources with comparable speed.

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Dynamic Optimization of Provider-Based Scheduling for HPC Workloads

Dynamic Optimization of Provider-Based Scheduling for HPC Wo...

引用

International Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Jacopo Marino Fulvio Risso Mauro Bighi Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy Dept. of Information Technology PUNCH Torino S.p.A Torino Italy

The vast array of cloud providers present in today’s market proffer a suite of High-Performance Computing (HPC) services. However, these offerings are characterized by significant variations in execution times and cost structures. Consequently, selecting the optimal cloud provider and configuring the features of the chosen computing instance (e.g. virtual machines) proves to be a challenging task for users intending to execute HPC workloads. This paper introduces a novel component designed for effortless integration with existing HPC scheduling systems. This module’s primary function is to facilitate the selection of the most appropriate cloud provider for each distinct job, thereby empowering dynamic and adaptive cost-minimization strategies. Through the application of data augmentation techniques and the employment of Continuous Machine Learning, the system is endowed with the capability to operate efficiently with cloud providers that have not been previously utilized. Furthermore, it is capable of tracking the evolution of jobs over time. Our results show that this component can achieve consistent economic savings, based on the quality of the data used in the training phase.

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Pose-free visual servoing from 3D measurements

Pose-free visual servoing from 3D measurements

引用

European control Conference (ECC)

作者： Adrian Burlacu Radu L. Rosca Andrei I. Iancu Enric Cervera Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Romania Dept. of Computer Science and Engineering Jaume I University Spain

In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.

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High Efficiency and High Gain Hybrid DC-DC Converter with Switched Capacitor

High Efficiency and High Gain Hybrid DC-DC Converter with Sw...

引用

IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Brenna Theodora Machado Matos Rodrigues Mauricio Albuquerque Moura Edilson Mineiro Sá Junior Kleber Cesar Alves de Sousa Dept. Electrical and Computer Engineering Federal University of Ceara(UFC) Sobral Brazil Dept. Control and Industrial Processes Federal Institute of Caera Sobral Brazil

This work presents the study and development of a high-gain hybrid DC-DC converter with switched capacitor for photovoltaic energy applications. Qualitative analyzes and quantitative values of the converter are proposed. The proposed converter is based on the converter boost integrated into switched capacitive cells with the addition of a small inductor resonant. A mathematical modeling of the converter was developed to determine the value of the resonant inductance, where the converter was analyzed for inductance values of 1uH at 2uH. This proposal presented some advantages: such as extended static gain, reduction of voltage stress in semiconductors and reduction of current peaks in switches. A 200 W prototype was developed and its respective results are presented. Maximum efficiency obtained was 97.1% for a voltage gain of 10.

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Partial Discharge Classification With 1D Convolutional Neural Network

Partial Discharge Classification With 1D Convolutional Neura...

引用

International Conference on Properties and Applications of Properties and Applications of Dielectric Materials

作者： Thepjit Cheypoca Wiboon Promphanich Aung Ye Thway Angelina Phimpissada Hankae Siwakorn Jeenmuang Norasage Pattanadech Instrumentation and Control Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Computer Engineering Dept. School of EngineeringKing Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Electrical Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Mechatronics Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350374605

ISBN: (纸本)9798350386165

This paper introduces a novel approach for classifying with the 1D Convolutional Neural Network model for partial discharge patterns, that consists of corona discharge, surface discharge and internal discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The Artificial Neural Network for the classification model was constructed. Moreover, 2×1D CNN feature extraction was utilized to reduce the curse of dimensionality in the dense layer of the proposed PD classification model. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed.

关键词： Partial discharges Partial discharge measurement Surface discharges Neurons Training data Discharges (electric) Data models Convolutional neural networks Integrated circuit modeling Testing

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Partial Discharge Classification with Transformer Neural Networks

Partial Discharge Classification with Transformer Neural Net...

引用

International Conference on Properties and Applications of Properties and Applications of Dielectric Materials

作者： Thepjit Cheypoca Wiboon Promphanich Aung Ye Thway Angelina Phimpissada Hankae Siwakorn Jeenmuang Norasage Pattanadech Instrumentation and Control Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Computer Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Electrical Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Mechatronics Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350374605

ISBN: (纸本)9798350386165

This paper introduces an approach with the Transformer Neural Networks model for partial discharge patterns classification, that consists of corona discharge, internal discharge and surface discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The phase value will be encoded into the charge array and Transformer Neural Network is constructed using Positional Embedding and Transformer Encoder Layer. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed

关键词： Partial discharges Phased arrays Partial discharge measurement Surface discharges Training data Pattern classification Transformers Discharges (electric) Biological neural networks Testing

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Integration of a multi-rate electron density profile observer in the plasma control system of TCV 49

Integration of a multi-rate electron density profile observe...

引用

49th EPS Conference on Plasma Physics, EPS 2023

作者： Pastore, F. Felici, F. Sauter, O. Bosman, T.O.S.J. Galperti, C. Vincent, B. Pau, A. Poels, Y. Ravensbergen, T. Vu, N.M.T. Lausanne Switzerland DIFFER - Dutch Institute for Fundamental Energy Research Energy Systems and Control Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mechanical Engineering Control Systems Technology Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mathematics and Computer Science Data Mining Group Eindhoven Netherlands ITER Organization Route de Vinon-sur-Verdon St. Paul Lez Durance13067 Cedex France

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FPGA-based Low Power Acceleration of HARK Sound Source Localization

FPGA-based Low Power Acceleration of HARK Sound Source Local...

引用

IEEE Cool Chips

作者： Zirui Lin Katsutoshi Itoyama Kazuhiro Nakadai Hideharu Amano Dept. of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Honda Research Institute Japan Co. Ltd. Saitama Japan Dept. of Information and Computer Science Keio University Kanagawa Japan

ISBN: (数字)9798350384147

ISBN: (纸本)9798350384154

This paper presents an FPGA-based low-power acceleration of sound source localization in HARK, open-source software for robot audition. Due to the massive matrix operations, sound source localization in HARK takes substantial processing time in edge computing devices. To balance processing time and low power consumption, two functions in sound source localization that include many matrix operations are targeted and migrated on an FPGA SoC board called M-KUBOS. Compared to CPU-based computing on ARM Cortex A53, our implementation achieved a 2.0× speedup and 1.7× lower energy consumption.

关键词： Location awareness Program processors Power demand Parallel processing Energy efficiency Matrix decomposition Robots

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Load Demand Prediction for Electric Vehicles Smart Charging through Consensus-based Federated Learning

Load Demand Prediction for Electric Vehicles Smart Charging ...

引用

Mediterranean Conference on control and Automation (MED)

作者： Danilo Menegatti Antonio Pietrabissa Sabato Manfredi Alessandro Giuseppi Dept. of Computer Control and Management Engineering (DIAG) University of Rome ”La Sapienza” Rome Italy Dept. of Electrical Engineering and Information Technology University of Naples ”Federico II” Naples Italy

Having access to a reliable and accurate prediction of the short-term power demand is a fundamental step for the widespread adoption of Electric Vehicles (EVs), as their charges may have a significant impact on the power system balancing. In this direction, we propose a short-term load demand predictor, based on distributed Long Short-Term Memory Networks, that employs consensus and fully-decentralized Federated Learning (FL) algorithms to seek cooperation among multiple points of charge without the requirement of sharing any user-related data.

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Linear Quadratic Regulator-based controller for control Mode Switching Under Fault Operation of Grid-Connected PV with Supercapacitor System

Linear Quadratic Regulator-based Controller for Control Mode...

引用

IEEE Energy Conversion Congress and Exposition, ECCE

作者： Paychuda Kritprajun Leon M. Tolbert Nattapat Praisuwanna Jingxin Wang Yunting Liu Maximiliano Ferrari Dept. of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA Dept. of Electrical Engineering The Pennsylvania State University PA USA Grid Components and Control Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper proposes a linear quadratic regulator (LQR)-based controller for a grid-connected photovoltaic (PV) with a supercapacitor (SC) system to ensure a smooth transition of control mode when the SC is unavailable (completely charged) during fault operations. The SC improves the low-voltage ride-through (LVRT) capability of the PV system by quickly balancing power between the PV system and the grid. When the SC reaches its full charge capacity, the DC-link voltage will be controlled by the inverter’s controller, and the PV system may need to curtail its power generation. During the transition, fluctuations in the DClink voltage can occur which can compromise the stability of the PV system, especially when the control mode switching happens during severe fault operations. The proposed LQR-based controller is validated on a hardware testbed platform to demonstrate its effectiveness in reducing DC-link overvoltage during the control mode transitions. As a result, the PV system can remain compliant with LVRT requirements while maintaining stability during fault operations.

关键词： Voltage fluctuations Regulators Power quality Power control Switches Power system stability Supercapacitors control systems Voltage control Transient analysis

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