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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 76 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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 Volume 17 (2017)
 
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FEATURED ARTICLE

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S.
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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  1/2015 - 4

FPGA-Based Embedded System Architecture for Micro-Genetic Algorithms Applied to Parameters Optimization in Motion Control

JAEN-CUELLAR, A. Y. See more information about JAEN-CUELLAR, A. Y. on SCOPUS See more information about JAEN-CUELLAR, A. Y. on IEEExplore See more information about JAEN-CUELLAR, A. Y. on Web of Science, MORALES-VELAZQUEZ, L. See more information about  MORALES-VELAZQUEZ, L. on SCOPUS See more information about  MORALES-VELAZQUEZ, L. on SCOPUS See more information about MORALES-VELAZQUEZ, L. on Web of Science, ROMERO-TRONCOSO, R. See more information about  ROMERO-TRONCOSO, R. on SCOPUS See more information about  ROMERO-TRONCOSO, R. on SCOPUS See more information about ROMERO-TRONCOSO, R. on Web of Science, OSORNIO-RIOS, R. A. See more information about OSORNIO-RIOS, R. A. on SCOPUS See more information about OSORNIO-RIOS, R. A. on SCOPUS See more information about OSORNIO-RIOS, R. A. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,535 KB) | Citation | Downloads: 428 | Views: 1,427

Author keywords
control design, genetic algorithms, field programmable gate arrays, microprocessors, servo systems

References keywords
genetic(22), algorithm(17), optimization(12), systems(9), design(8), controller(8), control(8), applications(7), system(6), implementation(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-02-28
Volume 15, Issue 1, Year 2015, On page(s): 23 - 32
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.01004
Web of Science Accession Number: 000352158600004
SCOPUS ID: 84924804553

Abstract
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Meta-heuristic techniques are powerful tools used to find an optimal solution for complex problems to which classical techniques find difficult to solve. The features among all the meta-heuristic techniques are the high amount of computational resources spent on their implementation and the computing effort generated on their execution. For this reason, many works have proposed their use on the base of software methodologies without achieving online or real-time performance. In the present work, two strategies that implement the Genetic Algorithms are presented by using the micro-population concept with the objective of reducing computational resources, increasing the heuristic search speed, and providing simplicity in its design. Both strategies are implemented in hardware architecture; the first, as a software strategy in a proprietary embedded processor, the second, as a hardware co-processor unit. In order to validate the proposed approaches, several tests to optimize a motion controller in a servo system are presented and compared with a classical tuning technique.


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Cited-By CrossRef

[1] Micro-genetic algorithms for detecting and classifying electric power disturbances, Jaen-Cuellar, Arturo Yosimar, Morales-Velazquez, Luis, Romero-Troncoso, Rene de Jesus, Moriñigo-Sotelo, Daniel, Osornio-Rios, Roque Alfredo, Neural Computing and Applications, ISSN 0941-0643, 2016.
Digital Object Identifier: 10.1007/s00521-016-2355-z
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Copyright ©2001-2017
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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