DefinePK

Abstract

This paper describes a study of tuning process for Fuzzy Logic Controller (FLC) and Proportional Integral Derivative (PID) controller design. A PID controller is ubiquitous; while simple in theory, but design and implementation of PID controllers can be difficult and time consuming in practice. In PID design, there are three approaches to determining the optimal tuning include manual tuning, tuning heuristics, and automated methods. In FLC design, there is no systematic procedure to tune fuzzy logic controller to follow a desired set point. The tuning process of FLC using trial-and-error approach is commonly done until satisfactory results are obtained. The performance of a FLC depends on its control rules and membership functions. A method is presented for tuning fuzzy control rules by manual tuning to make the system behave as closely as possible to the expert behavior in a control process. The tuning method fits the membership functions of the fuzzy rules given by the experts with the inference system and the defuzzification strategy selected and obtaining high-performance membership functions. This paper demonstrates a difference tuning process by tuning the PID and also adjusting the FLC membership function to get desired output.