Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 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


TRAFFIC STATS

1,531,488 unique visits
478,039 downloads
Since November 1, 2009



No robots online now


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
 Volume 14 (2014)
 
     »   Issue 4 / 2014
 
     »   Issue 3 / 2014
 
     »   Issue 2 / 2014
 
     »   Issue 1 / 2014
 
 
 Volume 13 (2013)
 
     »   Issue 4 / 2013
 
     »   Issue 3 / 2013
 
     »   Issue 2 / 2013
 
     »   Issue 1 / 2013
 
 
  View all issues  


FEATURED ARTICLE

ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
Issue 3/2016

AbstractPlus


SAMPLE ARTICLES

On the Optimality of Trust Network Analysis with Subjective Logic, PARK, Y.
Issue 3/2014

AbstractPlus

A Blind High-Capacity Wavelet-Based Steganography Technique for Hiding Images into other Images, HAMAD, S., KHALIFA, A., ELHADAD, A.
Issue 2/2014

AbstractPlus

Single-phase Multilevel Current Source Inverter with Reduced Device Count and Current Balancing Capability, MOALLEMI KHIAVI, A., FARHADI KANGARLU, M., DAIE KOOZEHKANANI, Z., SOBHI, J., HOSSEINI, S. H.
Issue 3/2015

AbstractPlus

A Framework for Hardware-Accelerated Services Using Partially Reconfigurable SoCs, MACHIDON, O. M., HINTEA, S., SANDU, F.
Issue 2/2016

AbstractPlus

Location of Fraudulent Branch Lines or Faults in Short-Length Low Voltage Lines, ESCOBEDO, J., MEDINA, A., HERNANDEZ, J.-C., ALMONACID, G., VIDAL, P.
Issue 3/2014

AbstractPlus

FIR Filter Sharpening by Frequency Masking and Pipelining-Interleaving Technique, CIRIC, M. P., RADONJIC, V. M., KRNETA, R. R., STEFANOVIC, N. J.
Issue 4/2014

AbstractPlus




LATEST NEWS

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 "Big Data - " 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.

2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

2015-Dec-04
Starting with Issue 2/2016, the article processing charge is 300 EUR for each article accepted for publication. The charge of 25 EUR per page for papers over 8 pages will not be changed. Details are available in the For authors section.

Read More »


    
 

  2/2012 - 5

Control of the Bed Temperature of a Circulating Fluidized Bed Boiler by using Particle Swarm Optimization

AYGUN, H. See more information about AYGUN, H. on SCOPUS See more information about AYGUN, H. on IEEExplore See more information about AYGUN, H. on Web of Science, DEMIREL, H. See more information about  DEMIREL, H. on SCOPUS See more information about  DEMIREL, H. on SCOPUS See more information about DEMIREL, H. on Web of Science, CERNAT, M. See more information about CERNAT, M. on SCOPUS See more information about CERNAT, M. on SCOPUS See more information about CERNAT, M. 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 (1,008 KB) | Citation | Downloads: 846 | Views: 3,117

Author keywords
particle swarm optimization, bed temperature, fuzzy logic, boiler

References keywords
swarm(25), optimization(21), control(20), controller(13), systems(11), fuzzy(9), evolutionary(7), computation(7), system(6), fluidized(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 27 - 32
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02005
Web of Science Accession Number: 000305608000005
SCOPUS ID: 84865280645

Abstract
Quick view
Full text preview
Circulating fluidized bed boilers are increasingly used in the power generation due to their higher combustion efficiency and lower pollutant emissions. Such boilers require an effective control of the bed temperature, because it influences the boiler combustion efficiency and the rate of harmful emissions. A Particle-Swarm-Optimization-Proportional-Integrative-Derivative (PSO-PID) controller for the bed temperature of a circulating fluidized bed boiler is presented. In order to prove the capability of the proposed controller, its performances are compared at different boiler loads with those of a Fuzzy Logic (FL) controller. The simulation results demonstrate some advantages of the proposed controller.


References | Cited By  «-- Click to see who has cited this paper

[1] B. Lixia, Z. Junxia, F. Song, Modeling and simulating of bed temperature control of circulating fluidized boiler, Journal of North China Electric Power University, vol. 30 n. 1, January 2003, pp. 53-56.

[2] P. Fu, X. Yu, H. Wang, Research on fuzzy control algorithm for bed temperature control of circulating fluidized bed boiler, Proceedings of the Forth International Conference on Machine Learning and Cybernetics, August 18-21, 2005, Guangzhou, China.
[CrossRef]


[3] A. A. Jalali, A. Hadavand, Bed temperature control of a circulating fluidized bed combustion system using H algorithm, Proceedings of the International Conference on Control, Automation and Systems, October 17-20, 2007, Seoul, South Korea.
[CrossRef] [SCOPUS Times Cited 3]


[4] M. Clerc, The swarm and the queen: towards a deterministic and adaptive particle swarm optimization, Proceedings of the Congress on Evolutionary Computation, July 6-9, 1999, Washington, DC, USA [PubMed]

[5] J. Kennedy, R. Eberhart, Particle swarm optimization, Proceedings of the IEEE International Conference on Neural Networks, November 27-December 1, 1995, Perth WA, Australia
[CrossRef] [Web of Science Times Cited 16623] [SCOPUS Record]


[6] J. Chen, Z. Ren, X. Fan, Particle swarm optimization with adaptive mutation and its application research in tuning of PID parameters, Proceedings of the 1st International Symposium on Systems and Control in Aerospace and Astronautics, January 2006, Harbin, China, pp. 19-21
[CrossRef]


[7] Y. Shi, R. C. Eberhart, Emprical study of particle swarm optimization, Proceedings of the Congress on Evolutionary Computation, July 6-9, 1999, Washington DC, USA [PubMed]

[8] H. Gozde, M. C. Taplamacioglu, I. Kocaarslan, E. Cam, Particle swarm optimization based load frequency control in a single area power system, Scientific Bulletin of Electronics and Computers Science, University of Pitesti, Romania, vol. 2 n. 8, 2008, pp. 106-110.

[9] Z.-L. Gaing, A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Transactions on Energy Conversion, vol. 19 n. 2, June 2004, pp. 384-391
[CrossRef] [Web of Science Times Cited 515] [SCOPUS Times Cited 798]


[10] J. Wang, Z. Zhai, Y. Jing, C. Zhang, Particle swarm optimization for redundant building cooling heating and power systems, Applied Energy, vol. 87, n. 12, 2010, pp. 3668-3679
[CrossRef] [Web of Science Times Cited 73] [SCOPUS Times Cited 91]


[11] H. Aygun, H. Demirel, Comparison of PSO-PID, FLC and PID in a circulating fluidized bed boiler, Proceedings of the 7th International Conference on Electrical and Electronics Engineering (ELECO'11), December 1-4, 2011, Bursa, Turkey.

[12] H. Aygun, Control of the bed temperature of a fluidized bed boiler by a Particle Swarm Optimization based PID (PSO-PID) controller, (in Turkish), M.S. Thesis, Electrical and Electronics Eng., 2011, Karabuk University, Karabuk, Turkey.

[13] A. Hadavand, A. A. Jalali, P. Famouri, An innovative bed temperature-oriented modelling and robust control of a circulating fluidized bed combustor, Chemical Engineering Journal, vol. 140, 2008, pp. 497-508
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 15]


[14] L. Changliang, S. Xiaojiao, Electromagnetism-like mechanism particle swarm optimization and application in thermal process model identification, Proceedings of the 2010 Chinese Control and Decision Conference (CCDC), 2010, pp.: 2966 - 2970
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[15] Chengxi Ma, Lin Qian, Ling Wang, M. I. Menhas, Minrui Fei, Determination of the PID controller parameters by Modified Binary Particle Swarm Optimization algorithm, Proceedings of the 2010 Chinese Control and Decision Conference (CCDC), 2010 , pp. 2689 - 2694
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 5]


[16] E. Masehian, D. Sedighizadeh, "Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning," Advances in Electrical and Computer Engineering, vol. 10, no. 4, pp. 69-76, 2010
[CrossRef] [Full Text] [Web of Science Times Cited 20] [SCOPUS Times Cited 25]


[17] Z. Dong Ze, Sun Jian, Wang Zijie, Sun Ming, PID-NN decoupling control of CFB boiler combustion system based on PSO method, Proceedings of the 9. International Conference on Sustainable Power Generation and Supply, SUPERGEN '09, 2009, pp. 1 - 6
[CrossRef] [SCOPUS Record]


[18] H. Tiryaki, A comparison between fuzzy logic controllers and PID controller used in an electrical thermal station, (in Turkish), Master Thesis, 2005, Kirikkale University, Kirikkale, pp. 20-30.

[19] H. Hu, Q. Hu, Lu Z., and D. Xu, Optimal PID controller design in PMSM servo system via particle swarm optimization, 31st Annual Conference of IEEE Industrial Electronics Society, Raleigh, 2005, pp. 79-83.
[CrossRef] [SCOPUS Times Cited 24]


[20] C. Ou, and W. Lin, Comparison between PSO and GA for parameters optimization of PID controller, Proceedings of the IEEE International Conference on Mechatronics and Automation, Luoyang, 2006, pp. 2471-2475.
[CrossRef] [SCOPUS Times Cited 64]


[21] N. Pillay, and P. Govender, A particle swarm optimization approach for model independent tuning of PID control loops, The 8th IEEE Africon Conference, Windhoek, 2007, pp. 1-7
[CrossRef] [SCOPUS Record]


[22] L. Xu-zhou, Y. Fei, and W. You-bo, PSO algorithm based online self tuning of PID controller, International Conference on Computational Intelligence and Security, Harbin, 2007, pp. 128-132.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[23] Z.-L. Gaing, A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Transactions on Energy Conversion, 19 (2), 2004, pp. 384-391
[CrossRef] [Web of Science Times Cited 515] [SCOPUS Times Cited 798]


[24] S. Ying, C. Zengqiang, and Y. Zhunhi, Adaptive constrained predictive PID controller via particle swarm optimization, Proceedings of the 26th Chinese Control Conference, Hunan, 2007, pp. 729-733.
[CrossRef] [SCOPUS Times Cited 1]


[25] Y.-L. Lin, W.-D. Chang,, and J.-G. Hsieh, A particle swarm optimization approach to nonlinear rational filter modeling", Expert Systems with Applications, 34 (2), 2004, pp. 1194-1199
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 63]


[26] W.-D. Chang, and S.-P. Shih, PID controller design of nonlinear systems using an improved particle swarm optimization approach, Communications in Nonlinear Science and Numerical Simulation, 15 (11), 2010, pp. 3632-3639
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 82]


[27] L. A. Zadeh, Outline of a new approach to the analysis of complex systems and decision processes, IEEE Transactions on Systems, Man and Cybernetics, SMC-3 (1), 1973, pp. 28-44
[CrossRef] [SCOPUS Times Cited 4376]


[28] E. H. Mamdani, Application of fuzzy algorithms for control of simple dynamic plant, Procedings of IEEE, 121 (12), 1974, pp: 1585-1588
[CrossRef]


[29] E. H. Mamdani, and S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies, 7 (1), 1975, pp. 1-13
[CrossRef] [Web of Science Times Cited 2416]


[30] W. J. M. Kickert, and H. R. Lemke, Application of a fuzzy controller in a warm water plant, Automatica, 12 (4), 1976, pp. 301-308
[CrossRef] [Web of Science Times Cited 117] [SCOPUS Times Cited 135]


[31] H. Ying, The simplest fuzzy controllers using different inference methods are different nonlinear proportional-integral controllers with variable gains, Automatica, 29 (6), 1993, pp. 1579-1589
[CrossRef] [Web of Science Times Cited 78] [SCOPUS Times Cited 96]


[32] J. Ambuel, L. Steenhoek, R. Smith, and T. Colvin, Control of hydrostatic transmission output speed: development and comparision of PI and hybrid fuzzy-PI controllers, Transactions of the Asabe, 36 (4), 1993, pp. 1057-1064.

[33] S. Sugawara and T. Suzuki, Application of fuzzy control to air conditioning environment, Journal of Thermal Biology, 18, 1993, pp. 465-472
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 6]


[34] Y. Shi and R. C. Eberhart, A modified particle swarm optimizer, Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, 1998, pp. 69-73
[CrossRef] [Web of Science Times Cited 781]


[35] J. Chen, J., Z. Ren, and X. Fan, Particle swarm optimization with adaptive mutation and its application research in tuning of PID parameters, 1st International Symposium on Systems and Control in Aerospace and Astronautics, Harbin, 2006, pp. 990-994
[CrossRef]


[36] Y. Shi and R. C. Eberhart, Empirical study of particle swarm optimization, Proceedings of the Congress on Evolutionary Computation, Washington, 1999, pp. 1945-1950.
[CrossRef] [SCOPUS Times Cited 1457]


[37] R. C. Eberhart and Y. Shi, Tracking and optimizing dynamic systems with particle swarms, Proceedings of the Congress on Evolutionary Computation, Seoul, 2001, pp. 94-100.
[CrossRef]


[38] M. Clerc, The swarm and the queen: towards a deterministic and adaptive particle swarm optimization, Proceedings of the Congress on Evolutionary Computation, Washington, DC, 1999, pp. 1951-1957.
[CrossRef] [SCOPUS Times Cited 846]


[39] R. C. Eberhart and Y. Shi, Particle swarm optimization: developments, applications and resources, Proceedings of the Congress on Evolutionary Computation, Seoul, 2001, pp. 81-86.
[CrossRef]


[40] A. R. Mehrabian and C. Lucas, Automatic tuning of decentralized controllers by swarm intelligence, 3rd International IEEE Conference on Intelligent Systems, London, 2006, pp. 350-353
[CrossRef] [SCOPUS Times Cited 3]


[41] S. H. M. Amin and A. Adriansyah, Particle swarm fuzzy controller for behavior-based mobile robot, 9th International Conference on Control, Automation, Robotics and Vision, Singapore, 2006, pp. 1-6
[CrossRef] [SCOPUS Times Cited 3]


[42] Y. Meiying and W. Xiaodong, PSO-based Parameter Estimation of Nonlinear Systems, Proceedings of the 26th Chinese Control Conference, Hunan, 2007, pp. 533-536.
[CrossRef] [SCOPUS Record]




References Weight

Web of Science® Citations for all references: 21,243 TCR
SCOPUS® Citations for all references: 8,893 TCR

Web of Science® Average Citations per reference: 494 ACR
SCOPUS® Average Citations per reference: 207 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references background updated on 2017-02-19 06:52 in 206 seconds.




Note1: Web of Science® is a registered trademark of Thomson Reuters.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2017
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: