Genetic Iterative Feedback Tuning (GIFT) Method for Fuzzy Control System Development

Abstract

This paper proposes an original iterative feedback tuning (IFT) method employing genetic algorithms to develop a class of fuzzy control systems. The approach is based on using the linear case results from the original IFT method and on replacing the parameter update law by genetic algorithms. Then, these results are transferred to the fuzzy case in terms of the modal equivalence principle resulting in an attractive development method referred to as genetic iterative feedback tuning (GIFT). The GIFT method is applied to the development of fuzzy control systems with PI-fuzzy controllers dedicated to a class of integral type servo systems, where the linear case is focused on the IFT method in connection with the extended symmetrical optimum method to obtain the initial values of the linear PI controller parameters. Real-time experimental results corresponding to a fuzzy controlled nonlinear servo system are presented to validate the development method