CFP last date
20 May 2024
Reseach Article

Fuzzy Inference System to Control PC Power Failures

by V.Mary Sumalatha, K.V.Ramani, K.V.Lakshmi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 4
Year of Publication: 2011
Authors: V.Mary Sumalatha, K.V.Ramani, K.V.Lakshmi
10.5120/3377-4671

V.Mary Sumalatha, K.V.Ramani, K.V.Lakshmi . Fuzzy Inference System to Control PC Power Failures. International Journal of Computer Applications. 28, 4 ( August 2011), 10-17. DOI=10.5120/3377-4671

@article{ 10.5120/3377-4671,
author = { V.Mary Sumalatha, K.V.Ramani, K.V.Lakshmi },
title = { Fuzzy Inference System to Control PC Power Failures },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 4 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 10-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number4/3377-4671/ },
doi = { 10.5120/3377-4671 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:51.637925+05:30
%A V.Mary Sumalatha
%A K.V.Ramani
%A K.V.Lakshmi
%T Fuzzy Inference System to Control PC Power Failures
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 4
%P 10-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

If there is any one component that is absolutely vital to the operation of a computer, it is the power supply. Without it, a computer is just an inert box full of plastic and metal. The power supply converts the alternating current line to the direct current needed by the personal computer. This paper presents an application of fuzzy logic to control power failures in personal computers. The application uses fuzzy sets, fuzzy if-then rules and fuzzy inference system. Fuzzy logic is widely used to solve uncertain problems. Fuzzy inference systems (FIS) are widely used for process simulation or control. They can be designed either from expert knowledge or from data. For complex systems, FIS based on expert knowledge only may suffer from a loss of accuracy. This is the main incentive for using fuzzy rules inferred from data.

References
  1. L. A. Zadeh, “Fuzzy sets,” Inform. Control, vol. 8, pp. 338– 353, 1965.
  2. E. H. Mamdani and S. Assilian, “An experiment in linguistic synthesis with a fuzzy logic controller,” Int. J. Man-Mach. Stud., vol. 7, pp. 1–13, 1975.
  3. E.W. Gunther and H. Mehta, “A Survey of Distribution System power Quality – Preliminary Results”, IEEE Transactions on Power Delivery, Vol. 10, No.1, pp. 322-329, January 1995.
  4. K.Tanaka, An Introduction to Fuzzy Logic fro practical Applications, Springer-Verlag New York, Inc., New York, NY, USA, 1997.
  5. Mamdani, E.H. and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller," International Journal of Man-Machine Studies, Vol. 7, No. 1, pp. 1-13, 1975.
  6. Jang, J.-S. R. and C.-T. Sun, Neuro-Fuzzy and Soft Computing: AComputational Approach to Learning and Machine Intelligence, Prentice Hall, 1997.
  7. Sugeno, M., Industrial applications of fuzzy control, Elsevier Science Pub. Co., 1985
  8. “Fuzzy logic toolbox user’s guide”, The MathWorks Inc., 1999.
  9. Fuzzy logic in power system performability. Dumitrescu M, Munteanu T, Ulmeanu A P. Intelligent Systems, 2004. Proceedings, 2004 2nd International IEEE conference. pages 326-330 vol1.
  10. A Fuzzy Logic application to represent Load sensitivity to voltage sags. Bonatto, B.D.; Niimura,T.; Dommel,H.W.; Hamonics and quality of power, 1998, proceedings. 8th International conference, Pages 60-64, vol1.
  11. Lighting protection of power systems using fuzzy logic techniques. Orille, A.L.; Bogarra, S.; Grau, M.A.; Iglesias, J.; Fuzzy systems, 2003.FUZZ’03. 12th IEEE international conference, Volume: 2
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy sets Fuzzy if-then rules Fuzzy logic Fuzzy inference systems Mamdani Fuzzy modeling