This chapter presents the basics of fuzzy logic control, as well as the method of generating a membership function matrix for a fuzzy rule base. In fuzzy logic control the task of generating control decisions is computer automated, thereby alleviating the problems of control speed and facilitating simultaneous monitoring and control of many variables. The output decision of a fuzzy logic controller is a fuzzy value and is represented by a membership function. Because low-level control actions are typically crisp, the control inference must be defuzzified for actuation purposes. Several methods are available for defuzzification of a fuzzy control inference. The centroid method uses the entire membership function of a control inference. Thus, the defuzzified value depends on both size and shape of the membership function. The mean of maxima method depends only on the peak values of the control inference membership function. It is therefore independent of the membership function shape, and particularly its asymmetry.