INFORMATION CHANGE THE WORLD

International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.5, No.1, Dec. 2012

Performance Evaluation of Mamdani-type and Sugeno-type Fuzzy Inference System Based Controllers for Computer Fan

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Author(s)

Philip A. Adewuyi

Index Terms

Fuzzy Logic, Inference System, Controller, Rule-Based Operation, Computer Fan

Abstract

Nowadays, there are several models of computer systems finding their ways into various offices, houses, organizations as well as remote locations. Any slight malfunction of the computer system’s components could lead to loss of vital data and information. One of the sources of computer system malfunction is overheating of the electronic components. A common method of cooling a computer system is the use of cooling fan(s). Therefore, it is essential to have an appropriate control mechanism for the operation of computer system’s cooling fan in order to save energy, and prevent overheating. Failure to adopt a well designed and efficient performance controller could lead to the malfunction of a computer system. Presently, most controllers in computer systems are pulse width modulation based. That is, they make use of pulses in form of digits, 0 and 1. It was observed that inherent noise is still prevalent in the operation of computer system. Also, eventual breakdown of components is common. A new approach is therefore investigated through the use of fuzzy logic to serve as a base or platform to build an intelligent controller using a set of well defined rules to guide its operational performance. Mamdani-type fuzzy inference system and Sugeno-type fuzzy inference system were used with two input sets each and a single output function each. Simulation was carried out in MATLAB R2007a platform and operational performances of the two approaches were compared. Simulated results of the performances of the Mamdani-type fuzzy inference system based controller and the Sugeno-type fuzzy inference system based controller are presented accordingly.

Cite This Paper

Philip A. Adewuyi,"Performance Evaluation of Mamdani-type and Sugeno-type Fuzzy Inference System Based Controllers for Computer Fan", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.1, pp.26-36, 2013.DOI: 10.5815/ijitcs.2013.01.03

Reference

[1]Computer. An article retrieved from http://www.merricanwebster.com/dictionary/computer. 13th September, 2012.

[2]M. Boris, “Case Cooling-the physics of god airflow”, an article retrieved fromhttp://www.technibble.com/case-cooling-the-physics-of-good-airflow/2/. 13th September, 2012.

[3]Wikipedia, “Computer Fan”, Article retrieved from www.en.m.wikipedia.org/wiki/computer_fan.com. June 2012.

[4]A. Kaufmann and M. M. Gupta, “Introduction to Fuzzy Arithmetic Theory and Application”, Van Nostrand Reinhold, New York, 1991.

[5]G.J. Klir and Bo Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, Upper Saddle River, NJ, 1995.

[6]A. Kaur and A. Kaur(2012) “Comparison of Mamdani-Type and Sugeno-Type Fuzzy Inference System for Air Conditioning System”, International Journal of Soft Computing and Engineering, May 2012, Vol. 2, Iss. 2, pp. 2231 – 2307. 

[7]A. Kaur and A. Kaur(2012) “Comparison of Fuzzy Logic and Neuro-Fuzzy Algorithms for Air Conditioning System”, International Journal of Soft Computing and Engineering, March 2012 Vol. 2, Iss. 1, pp. 2231 – 2307.

[8]V.M. Sumalatha, K.V.Ramani, and K.V.Lakshmi, “Fuzzy Inference System to Control PC Power Failures”, International Journal of Computer Applications, Vol. 28, No 4,.

[9]D. D. Neema, R.N. Patel, and A. S. Thoke, “Speed Control of Induction Motor using Fuzzy Rule Base”, International Journal of Computer Applications, November 2011, Vol. 33, No 5.

[10]V. Chitra, and R. S. Prabhakar, “Induction Motor Speed Control using Fuzzy Logic Controller”, World Academy of Science, Engineering and Technology, 2006, Vol. 23, pp. 17-22.