Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

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: 77 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

1,718,915 unique visits
505,909 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 17 (2017)
 
     »   Issue 3 / 2017
 
     »   Issue 2 / 2017
 
     »   Issue 1 / 2017
 
 
 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
 
 
  View all issues  


FEATURED ARTICLE

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S.
Issue 3/2017

AbstractPlus






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.

Read More »


    
 

  3/2012 - 10

State-Space GMDH Neural Networks for Actuator Robust Fault Diagnosis

MRUGALSKI, M. See more information about MRUGALSKI, M. on SCOPUS See more information about MRUGALSKI, M. on IEEExplore See more information about MRUGALSKI, M. on Web of Science, WITCZAK, M. See more information about WITCZAK, M. on SCOPUS See more information about WITCZAK, M. on SCOPUS See more information about WITCZAK, 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 (1,050 KB) | Citation | Downloads: 420 | Views: 3,062

Author keywords
fault diagnosis, robustness, actuators, neural networks, system identification

References keywords
fault(14), control(12), systems(11), neural(10), witczak(7), networks(7), estimation(7), mrugalski(6), korbicz(6), gmdh(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 65 - 72
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03010
Web of Science Accession Number: 000308290500010
SCOPUS ID: 84865856659

Abstract
Quick view
Full text preview
Most fault diagnosis methods focus on the fault detection of the system or sensors and do not take into account the problem of the fault detection and isolation of the actuators, which are an important part of the contemporary industrial systems. To solve such a problem, the system outputs and inputs estimator based on a dynamic Group Method of Data Handling neural network in the state-space representation is proposed. In particular, the methodology of the adaptive thresholds calculation for system inputs and outputs is presented. The approach is based on the application of the Unscented Kalman Filter and Unknown Input Filter is presented. This result enables performing robust fault detection and isolation of the actuators. The final part of the paper presents an application study, which confirms the effectiveness of the proposed approach.


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

[1] R. Aarenstrup, "DC motor model," June 2012. [Online] Available: Temporary on-line reference link removed - see the PDF document

[2] D. Berdjag, V. Cocquempot, C. Christophe, A. Shumsky, and A. Zhirabok, "Algebraic approach for model decomposition: application to fault detetion and isolation in discrete-event systems," International Journal of Applied Mathematics and Computer Science, vol. 21, pp. 109-125, 2011.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 6]


[3] M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki, Diagnosis and Fault-Tolerant Control. Berlin, Heidelberg, New York: Springer-Verlag, 2003.

[4] S. De Oca, V. Puig, M. Witczak, and £. Dziekan, "Fault-tolerant control strategy for actuator faults using lpv techniques: Application to a two degree of freedom helicopter," International Journal of Applied Mathematics and Computer Science, vol. 22, no. 1, pp. 161-171, 2012.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 54]


[5] S. Ding, Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. Berlin/Heidelberg: Springer-Verlag, 2008.

[6] S. Gillijns and B. D. Moor, "Unbiased minimum-variance input and state estimation for linear discrete-time systems," Automatica, vol. 43, pp. 111-116, 2007.
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 173]


[7] S. Haykin, Kalman Filtering and Neural Networks. New York: John Wiley & Sons, 2001.
[CrossRef]


[8] S. Haykin, Neural Networks and Learning Machines. New York: Prentice Hall, 2009.

[9] R. Isermann, Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance. Heidelberg/Berlin: Springer-Verlag, 2005.

[10] A. Ivakhnenko and J. Mueller, "Self-organization of nets of active neurons," System Analysis Modelling Simulation, vol. 20, pp. 93-106, 1995.

[11] S. Julier and J. Uhlmann, "Unscented filtering and nonlinear estimation," Proceedings of the IEEE, vol. 92, no. 3, pp. 401-422, 2004.
[CrossRef] [Web of Science Times Cited 2259] [SCOPUS Times Cited 3475]


[12] T. Kondo and J. Ueno, "Nonlinear system identification by feedback gmdh-type neural network with architecture self-selecting function," in Intelligent Control (ISIC), 2010 IEEE International Symposium on, sept. 2010, pp. 1521-1526.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 2]


[13] J. Korbicz and M. Mrugalski, "Confidence estimation of gmdh neural networks and its application in fault detection system," International Journal of System Science, vol. 39, no. 8, pp. 783-800, 2008.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 19]


[14] J. Korbicz, M. Witczak, and V. Puig, "Lmi-based strategies for designing observers and unknown input observers for non-linear discrete-time systems," Technical Sciences, vol. 55, no. 1, pp. 31-42.

[15] L. Kral and M. Simandl, "Functional adaptive controller for multivariable stochastic systems with dynamic structure of neural network," Adaptive Control and Signal Processing, vol. 25, pp. 949-964, 2011.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 7]


[16] T. Lee and Z. Jiang, "On uniform global asymptotic stability of nonlinear discrete-time systems with applications," IEEE Trans. Automatic Control, vol. 51, no. 10, pp. 1644-1660, 2006.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 24]


[17] L. Ljung, System Identification: Theory for the User. Upper Saddle River, New York: Prentice Hall PTR, 1999.

[18] M. Mrugalski and J. Korbicz, "Gmdh neural networks," in The Industrial Electronics Handbook, 2nd ed., B. Wilamowski and J. Irwin, Eds. Boca Raton: CRC Press, Taylor Francis Group, 2011, vol. 5, pp. 8-1-8-21.

[19] M. Mrugalski, J. Korbicz, and R. Patton, "Robust fault detection via gmdh neural networks," Proceedings of 16th IFAC World Congress, IFAC, 2005.

[20] M. Mrugalski and M. Witczak, "Parameter estimation of dynamic gmdh neural networks with the bounded-error technique," J. Appl. Comput. Sci, vol. 10, no. 1, pp. 77-90, 2002.

[21] M. Mrugalski, M. Witczak, and J. Korbicz, "Confidence estimation of the multi-layer perceptron and its application in fault detection systems," Engineering Applications of Artificial Intelligence, vol. 21, no. 6, pp. 895-906, 2008.
[CrossRef]


[22] H. Niemann, "A model-based approach to fault-tolerant control," International Journal of Applied Mathematics and Computer Science, vol. 22, no. 1, pp. 67-86, 2012.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 24]


[23] H. Noura, D. Theilliol, J. Ponsart, and A. Chamseddine, Fault-tolerant Control Systems: Design and Practical Applications. London: Springer-Verlag, 2009.

[24] R. Patton, P. Frank, and R. Clark, Non-linear Systems Identification. From Classical Approaches to Neural Networks and Fuzzy Models. Berlin: Springer-Verlag, 2000.

[25] I. Peddle, "Discrete state space control," Control Systems, vol. 414, pp. 2-3, 2007.

[26] T. Senguler and E. K. amd S. Seker, "A new mlp approach for the detection of the incipient bearing damage," Advances in Electrical and Computer Engineering, vol. 10, no. 3, pp. 34-39, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 10]


[27] O. Straka, J. Dunik, and M. Simandl, "Truncation nonlinear filters for state estimation with nonlinear inequality constraints," Automatica, vol. 48, pp. 273-286, 2012.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 34]


[28] B. Teixeira, L. Torres, L. Aguirre, and D. Bernstein, "On unscented kalman filtering with state interval constraints," Journal of Process Control, vol. 20, no. 1, pp. 45-57, 2010.
[CrossRef] [Web of Science Times Cited 33] [SCOPUS Times Cited 48]


[29] M. Witczak, Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems. From Analytical to Soft Computing Approaches. Berlin: Springer-Verlag, 2007.

[30] M. Witczak, J. Korbicz, M. Mrugalski, and R. Patton, "A gmdh neural network based approach to robust fault detection and its application to solve the damadics benchmark problem," Control Engineering Practice, vol. 14, no. 6, pp. 671-683, 2006.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 68]


[31] M. Witczak and P. Pretki, "Design of an extended unknown input observer with stochastic robustness techniques and evolutionary algorithms," International Journal of Control, vol. 80, no. 5, pp. 749-762, 2007.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 34]


References Weight

Web of Science® Citations for all references: 2,633 TCR
SCOPUS® Citations for all references: 3,978 TCR

Web of Science® Average Citations per reference: 85 ACR
SCOPUS® Average Citations per reference: 128 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 updated on 2017-09-22 09:32 in 115 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: