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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

共 15474 条记录，以下是4891-4900 订阅

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Design considerations for monolithic integration of a micro hotplate temperature controller in a MEMS gas sensor

Design considerations for monolithic integration of a micro ...

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international conference on electrical engineering, computing science and automatic control (CCE)

作者： S. Mendoza-Acevedo M. A. Reyes-Barranca L. M. Flores-Nava A. Ávila-García J. L. González-Vidal Department of Electrical Engineering CINVESTAV Mexicali Mexico Universidad Autonoma del Estado de Hidalgo Pachuca Hidalgo Mexico

A control system to regulate the temperature of the micro hotplate in a MEMS gas sensor is presented. The controlelement, called micro hotplate, is comprised of a micro heater and a temperature sensor, both made with polysilicon, located near each other. This material has a Temperature Coefficient of Resistance (TCR) that is the basis for the design of the temperature controller of the gas sensor system. A high temperature between 250 and 400°C is needed to produce a chemical reaction between the gas and the sensing film, hence a reliable temperature control for the micro hotplate is desired. Thermal insulation of the circuitry from the heating element, having a monolithic sensor system, and low power consumption, are the main specifications for the system. This is obtained by means of a micro pit realized with MEMS micromachining processes. The analysis of the circuit proposed to fulfill these characteristics is presented, for its future integration with a standard CMOS technology. A trade off is established between the sensor structure parameters and the circuit design.

关键词： Monolithic integrated circuits Temperature sensors Temperature control Micromechanical devices Gas detectors control systems CMOS technology Chemicals Power system reliability Insulation

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Hybrid control based on a novel fast convergence and high precision CMAC for electric loading system

Hybrid control based on a novel fast convergence and high pr...

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9th international conference on Electronic Measurement and Instruments, ICEMI 2009

作者： Yang, Bo Wang, Zhe School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781424438624

A novel CMAC hybrid control strategy with fast convergence and high precision is proposed for the electric loading system of UAVs in order to solve disturbance of the surplus torque. This CMAC control strategy employs a nonuniform memory quantization scheme that defines its computing structure. A weighted Gaussian neighborhood-based activation process is subsequently implemented to facilitate the learning and computation of this novel CMAC structure. The hybrid controller is compound of CMAC and PD algorithm. The feedforward control is realized by CMAC while the feedback control is performed by PD controller. The mathematical model of an electric loading system for UAVs is established and the detailed control structure is put forward. Simulation results show that the proposed controller has a faster convergence rate and higher precision compared with the conventional CMAC, and can effectively eliminate the surplus torque and fairly improve the dynamic loading performance of the system. ©2009 IEEE.

关键词： Feedforward control

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Single Sample Face Recognition: A Comparative Study between Texture and Deep-Learning-based Features 21

Single Sample Face Recognition: A Comparative Study between ...

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21st IEEE international conference on sciences and Techniques of automatic control and Computer engineering, STA 2022

作者： Adjabi, Insaf Benzaoui, Amir University of Akli Mohand Oulhadj Computer Science Department Bouira10000 Algeria University of August 20 1955 Electrical Engineering Department Skikda21000 Algeria

ISBN: (纸本)9781665482615

Single sample face recognition (SSFR) is an active and challenging research subject in the biometric and artificial intelligence communities with the ultimate objective of recognizing individuals using only one facial image per class in the training set. Arguably, feature extraction is the crucial phase in constructing any pattern recognition system, which aims to extract the relevant information that characterizes each pattern. Texture and deep-learning-based approaches are the most prominent strategies for extracting relevant information. This paper compares several SSFR models constructed with texture and deep-learning-based features. We tested four common texture descriptors and seven pre-trained deep learning-based convolutional neural networks (CNNs) models to extract the discriminating face features. Finally, based on the K-Nearest Neighbor (K-NN) classifier, we performed the classification process. The results of the experiments on the unconstrained Alex & Robert (AR) dataset showed superior performance using texture-based approaches compared to the deep-learning-based strategies. © 2022 IEEE.

关键词： Face recognition

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Robust output feedback interpolation based control for constrained linear systems

Robust output feedback interpolation based control for const...

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8th international conference on Informatics in control, Automation and Robotics, ICINCO 2011

作者： Nguyen, Hoai-Nam Olaru, Sorin Gutman, Per-Olof Hovd, Morten - Automatic Control Department Gif sur Yvette France Faculty of Civil and Environmental Engineering Technion - Israel Institute of Technology Haifa Israel Department of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9783642313523

In this paper, we consider the robust output feedback problem for constrained linear systems. A novel interpolation based control scheme is introduced, which guarantees feasibility and robust asymptotically stable closed loop behavior despite the presence of constraints on the input and output variables and the presence of the additive and bounded disturbances. A solution to the problem of the state representation is provided through the use of stored input values and the measured past outputs. © 2013 Springer-Verlag.

关键词： Interpolation

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Performance Development of Industrial Automation with Multi Processing controller 2

Performance Development of Industrial Automation with Multi ...

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2nd IEEE international conference on Distributed computing and electrical Circuits and Electronics, ICDCECE 2023

作者： Karunakaran, V. Shashikala, H.K. Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

The industrial automation with multi processing controller is a technology that has revolutionized the way that industrial processes are managed. It has enabled the automation of complex and varied processes, allowing factories to become more efficient and productive. Multi processing controllers are powerful computers that are used to control and monitor a wide range of industrial processes. They are typically connected to a network of sensors and actuators that measure and control the physical environment. By connecting these components to a powerful computer, a multi-processing controller can be used to quickly and accurately adjust the physical environment in order to achieve desired results. A multi-processing controller can be used to control the temperature, pressure, and flow of a production line. By adjusting the temperature and pressure of a certain process, the controller can ensure that the material reaches the desired state. This can be done with a simple push of a button, eliminating the need for manual labor. Multi processing controllers also allow for the automation of complex tasks, such as the management of an entire production line. By connecting different components to the controller, it can be programmed to coordinate the entire production line, ensuring that the correct materials and processes are used at the right time. This eliminates the need for manual labor, as well as reduces the time and cost associated with production. © 2023 IEEE.

关键词： controllers

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Research on electric differential for steering electric vehicles

Research on electric differential for steering electric vehi...

引用

Computer science and Information engineering, CSIE 2012

作者： Wang, Zitong Yao, Wei Zhang, Wei College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9783642302220

Without traditional mechanical differentials, electric vehicles need electric differentials to avoid slipping. This paper proposed a novel electric differential control strategy to solve the problem. According to the given speed and road conditions, target slip ratios can be calculated. Based on the closed-loop control, this strategy regulates torques of the driving wheels to follow the required slip ratios strictly. The simulation results indicate that it could realize differential for the two driving wheels. Meanwhile, compared with traditional mechanical differentials, the slip ratios of driving wheels and the risk of slipping are minimized. © 2012 Springer-Verlag GmbH.

关键词： Wheels

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Lightweight Parallel CNN To Classify COVID-19 Associated Pneumonia From Chest X-Ray

Lightweight Parallel CNN To Classify COVID-19 Associated Pne...

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international conference on electrical engineering, computing science and automatic control (CCE)

作者： Hafsa Binte Kibria Md. Ali Hossain Department of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

The global outbreak of the novel Coronavirus disease (COVID-19) has impacted millions of individuals, leading to widespread health, economic, and social consequences. Additionally, the overwhelming number of COVID-19 cases has strained healthcare facilities, underscoring the crucial need for timely and accurate detection of infected individuals to mitigate the pandemic’s impact. Inspired by the fact that existing deep learning models often rely on millions of parameters, rendering them unsuitable for resource-constrained devices, we developed a lightweight Parallel Convolutional Neural Network (PCNN) in this research. The model addresses the necessity for efficient COVID-19 pneumonia diagnostics from chest X-ray images by significantly reducing the number of parameters, resulting in a notable accuracy of 99.25% with 313k parameters. To further reduce parameters, separable convolution blocks were introduced, yielding an accuracy of 99.21% with 224k parameters. Despite their lightweight nature, our model demonstrates competitive performance compared to heavyweight models, emphasizing an accuracy rate of 99.21%. By minimizing computational costs and memory requirements, our model offers a cost-effective solution that can be effortlessly deployed on devices with limited resources.

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Transport mechanisms in porous silicon layer and ZnO/PSL heterostructures

Transport mechanisms in porous silicon layer and ZnO/PSL het...

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international conference on electrical engineering, computing science and automatic control (CCE)

作者： M. A. Vásquez-A G. García-Salgado G. Romero-Paredes y R. Peña-Sierra Department of Electrical Engineering SEES del CINVESTAV-IPN Mexicali Mexico Department of Electrical Engineering SEES del CINVESTAV-IPN Mexico D.F. Mexico Centro de Investigación en Dispositivos Semiconductores BUAP. Puebla. Pue. México

The transport mechanisms in both silicon porous layers (PSL) and ZnO/PSL/c-Si heterostructures were identified by Current-Voltage (I-V) measurements. The PSL were made by anodic etching of p-type (100) Silicon (Si) wafers with resistivity of 1-5 ¿-cm. The heterostructures were manufactured by depositing a zinc oxide (ZnO) film by DC-sputtering on the previously obtained PSL. The measured electrical resistivity of the ZnO films and the PSL were of 5.3 × 10 5 and 5.7 × 10 7 ¿-cm, respectively. The current flow in the PSL is limited by the space-charge regions (SCL), due to the charge trapped in the distinct energy localized states. For the heterostructures similar results were found, where the dominant transport mechanisms are associated to the physical characteristics of the PSL and the ZnO films. Accordingly a bandgap diagram for ZnO/PSL heterostructure is proposed, where the participation of the variety of the defect levels are considered.

关键词： Silicon Zinc oxide Electrodes Current measurement Etching Conductivity Manufacturing Substrates Gold Luminescence

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Quantum computing Approaches to Optimal Power Flow in Complex Grid Networks

Quantum Computing Approaches to Optimal Power Flow in Comple...

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2023 international conference on Power Energy, Environment and Intelligent control, PEEIC 2023

作者： Boddu, Bhasker Krishna, M Hari Manjunatha Kumar, Nagendra Singh, Navdeep Lafta, Alaa M. Mlr Institute of Technology Department of Information Technology Telangana Hyderabad India Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Gl Bajaj Institute of Technology & Management Dept. of Eee U.P. Greater Noida India Lovely Professional University Phagwara India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350357769

Power flow optimization is paramount in ensuring reliable and efficient operation of electrical grid networks, especially as grids become more intricate with the integration of renewable energy sources. Classical computing methods have long dominated this optimization space but are increasingly challenged by the scalability and computational complexity of contemporary grid systems. This paper introduces a pioneering methodology leveraging the inherent capabilities of quantum computing to tackle optimal power flow (OPF) problems in multifaceted grid networks. Quantum algorithms, characterized by their superposition and entanglement properties, are harnessed to explore the vast solution space more efficiently than their classical counterparts. A quantum annealing approach, combined with the quantum phase estimation algorithm, is employed to ascertain global optima with reduced computational resources and time. Results obtained from simulated quantum environments, benchmarked against classical algorithms, demonstrate a significant reduction in computational time and enhanced accuracy in determining optimal solutions. This work elucidates the potential of quantum computing as a transformative tool in advancing the realms of grid optimization, setting a paradigm for future research in quantum-enabled energy systems. © 2023 IEEE.

关键词： Complex Grid Networks Optimal Power Flow Quantum Annealing Quantum computing Quantum Phase Estimation. Top of Form

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Robust and Predictive Charging of Large Electric Vehicle Fleets in Grid Constrained Parking Lots 14

Robust and Predictive Charging of Large Electric Vehicle Fle...

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14th IEEE international conference on Communications, control, and computing Technologies for Smart Grids, SmartGridComm 2023

作者： Hoogsteen, Gerwin Winschermann, Leoni Nijenhuis, Bart Arias, Nataly Banol Hurink, Johann L. University of Twente Dept. of Electrical Engineering Mathematics and Computer Science Enschede Netherlands

ISBN: (纸本)9781665455541

Grid congestion forms an obstacle for the adoption of electric vehicles (EVs) by companies for their sustainability goals. This paper presents a robust approach to smart charging of large fleets of EVs that only utilizes currently available technologies and data, such that it can be applied in practice. The method relies only on available data at charge point operators. The presented approach uses offline aggregated planning to determine a robust fill-level. Subsequently, this fill-level is used in online control to maximise the quality of service to users while being able to provide flexibility to the energy system. Simulation results using real data show that the self-consumption of PV energy can be improved from 72.0% to 85.4%. Furthermore, the energy not served is reduced from 5.9% to 2.8%. © 2023 IEEE.

关键词： Charging (batteries)

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