Evolutionary optimization of a motorcycle traction control system based on fuzzy logic.

Abstract

Braking and traction control systems are fundamental vehicle safety equipments. The first ones prevent the wheels from locking, maintaining, when possible, the handling of the vehicle under emergency braking. While the second ones control wheel slip when excessive torque is applied on driving wheels. The aim of this work is to develop and implement a new control model of a traction control system to be installed on a motorcycle, regulating the slip in traction and improving dynamic behavior of two-wheeled vehicles. This paper presents a novel traction control algorithm which makes use of a fuzzy logic control block. Two strategies to create the control block have been carried out. In the first one, the parameters that define the fuzzy logic controller have been tuned according to experience. In the second one, the parameters have been obtained by means of an Evolutionary Algorithm (EA) in order to design an augmented traction controller. It has been proved that the use of EA can improve the fuzzy logic based control algorithm, obtaining better results than those produced with the control tuned only by experience.