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

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.