Adaptive fuzzy controller using on-line genetic algorithm

A simple method is proposed to designing adaptive fuzzy controllers. This method is based on using of a modified immune genetic algorithm (MIGA) to tune the controller parameters. The design parameters include the scaling factors, the membership functions, and the rule base. The modification is based on extract good genes with the same value in both best parents in the population. These good genes are used in vaccination operation of the immune genetic algorithm (IGA). The effectiveness of the proposed method when decreasing or increasing the number of rules is investigated. In addition, the effectiveness when adaptation includes only inputs and outputs fuzzy controller parameters and or the rule base is illustrated. The proposed method is applied to an inverted pendulum system. Simulation results show the effectiveness of the adaptive technique.