CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

fuzzy Adaptive Controllers for Speed Control of PMSM Drive

by N. J. Patil, R. H. Chile, L. M. Waghmare
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 11
Year of Publication: 2010
Authors: N. J. Patil, R. H. Chile, L. M. Waghmare
10.5120/233-387

N. J. Patil, R. H. Chile, L. M. Waghmare . fuzzy Adaptive Controllers for Speed Control of PMSM Drive. International Journal of Computer Applications. 1, 11 ( February 2010), 94-101. DOI=10.5120/233-387

@article{ 10.5120/233-387,
author = { N. J. Patil, R. H. Chile, L. M. Waghmare },
title = { fuzzy Adaptive Controllers for Speed Control of PMSM Drive },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 11 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 94-101 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number11/233-387/ },
doi = { 10.5120/233-387 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:46:08.884192+05:30
%A N. J. Patil
%A R. H. Chile
%A L. M. Waghmare
%T fuzzy Adaptive Controllers for Speed Control of PMSM Drive
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 11
%P 94-101
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The objective of the Fuzzy Adaptive Control (FAC) is to tune the scaling factors of the direct fuzzy logic controller (FLC). In this novel approach output scaling factor of Fuzzy controller is tuned through adaptation mechanism. The idea is to have a control system that will be able to achieve improvement in tracking set point change and rejection of load disturbance. In this paper, the proposed Fuzzy Adaptive Controller is applied to a permanent magnet synchronous motor drive (PMSM). High performances and robustness have been achieved by using the FAC. This will be illustrated by simulation results and comparisons with other controllers such as PI; classical and fuzzy adaptive controller based on tuning of input and output scaling factors. The performance criteria selected is quadratic performance criteria in terms of Rise Time (RT), Settling Time (ST), Integral of square error (ISE) and Integral of absolute error (IAE).

References
  1. M. Kadjoudj, M.E. Benbouzid, C. Ghennai, and D. Diallo, 2004 A Robust hybrid current control for PMSM drives, IEEE trans. on Energy Conv. Vol. 19, No. 1, pp. 109-115.
  2. J.M. Mendel, 1995 Fuzzy logic systems for engineering, A tutorial, Proc. of the IEEE, Vol. 83 No. 3, pp. 345-377.
  3. L. Zhen, and L. Xu, 2000 Fuzzy learning enhanced speed control of an indirect field oriented control induction machine drive, IEEE Trans. on Control Systems Technology, Vol. 8, No. 2, pp. 270-278.
  4. J.L. Silva Neto, and H. Le Huy 1998 An improvement fuzzy learning algorithm for motion control applications, Proc. of the IEE, Vol. 1, pp. 1-5.
  5. M. Kadjoudj, R. Abdessemed, M.E. Benbouzid, and C. Ghennai 2000 Current control of PMSM fed by two and three levels VSI, in Proc. of EPE/PEMC, Tuke (Slovakia), Vol. 7,pp. 69-74.
  6. D.S. Reay, and M.W. Dunniganu 1997 Learning issues in model reference based fuzzy control, Proc. of the IEE Control Theory Application, Vol. 144, No. 6.
  7. M.A Henson, and D.E. Seborg 1990 Input- Output linearization of general non-linear processes, AIChE Journal, Vol.36, pp.1753-1757.
  8. W. A. Kwong, and K. Passino 1994 Fuzzy learning systems for aircraft control law reconfiguration, in Proc. IEEE Int. Symp. Intell. Contr., Columbus, OH, Aug. 16-18, pp. 333-338.
  9. W. A. Kwong, K. M. Passino, E. G. Lauknonen, and S. Yurkovich, 1995 Expert supervision of fuzzy learning systems for fault tolerant aircraft control, Proc. IEEE, Spec. Issue Fuzzy Logic Engg. Application, vol. 83, pp. 466-483.
  10. D.S. Reay, and M.W. Dunniganu 1997 Learning issues in model reference based fuzzy control, Proc. of the IEE Control Theory Application, Vol. 144, No. 6.
  11. J.T. Spooner, R. Ordonez and K.M. Passino1996 Stable direct adaptive control of a class of discrete time non-linear systems, Proc. of the 13th IFAC world congress, San Francisco, pp. 343-348.
  12. N. J. Patil, R.H. Chile and L. M. Waghmare 2007 Model Reference Adaptive Fuzzy Controller, Proc. of the International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007, Vol. 1, pp.100-104.
  13. K. Pal, R.K.Mudi and N.R.Pal 2002 A new scheme for fuzzy rule-based system identification and its application to self-tuning fuzzy controllers, IEEE trans. on Systems Man and Cybernetics vol.32, pp. 470-482.
  14. P. Pillay and R. Krishnan 1987 Application characteristics of PM Synchronous and BLDC servo drives, Conf. Record, IEEE IAS Annual meeting, Atlanta, pp. 380-390.
  15. Seema Chopra, R. Mitra and Vijay Kumar 2008 Auto Tuning of Fuzzy PI Type Controller Using Fuzzy Logic , International Journal of Computational Cognitin, Vol. 6, No. 1, pp 12-18.
  16. Seema Chopra, R. Mitra and Vijay Kumar 2006 Analysis of Fuzzy PI and PD type controllers using subtractive clustering, International Journal on Computational Cognition, Vol 4, No. 2, pp 30-34.
  17. Mohamed Kadjoudj1, Noureddine Golea1, Mohamed El Hachemi Benbouzid 2007, Fuzzy Rule - Based Model Reference Adaptive Control for PMSM Drives, Serbian Journal of Electrical Engineering Vol. 4, No. 1, 13-22.
  18. Seema Chopra, R. Mitra and Vijay Kumar 2005 Fuzzy Controller: Choosing an Appropriate and Smallest Rule Set , International Journal on Computational Cognition, Vol 2, No. 4, pp 73-79.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Logic Adaptive Control PMSM Drive PI Controller

Powered by PhDFocusTM