Genetic algorithm based fuzzy logic control for a magneto-rheological suspension

Abstract

To overcome the limitations of conventional fuzzy logic control strategies, an adaptive fuzzy logic control based on a hybrid Taguchi genetic algorithm is proposed to control the vibration of the magneto-rheological suspension in order to promote ride comfort. A half-car model equipped with two telescopic magneto-rheological dampers is first developed. An adaptive fuzzy logic control based on a hybrid Taguchi genetic algorithm is then formulated on the basis of the developed model. The hybrid Taguchi genetic algorithm is applied to tune the linguistic variables and control rules of the fuzzy logic control. Finally, a road test is carried out to validate the proposed control scheme. For comparison purposes, a conventional fuzzy logic control is also implemented on the test car. The results show that the magneto-rheological suspension system with two control strategies can improve ride comfort, and the proposed control algorithm has better ride improvement than conventional fuzzy logic control.