Speed-adaptive roll-angle-tracking control of an unmanned bicycle using fuzzy logic

This paper presents the development of dynamic equations and roll-angle-tracking controller of an unmanned bicycle. First, the equations of motion and constraints of a bicycle with rolling-without-slipping contact condition between wheels and ground are developed using Lagrange's equations. The equations are then used to implement the simulation of the bicycle dynamics. With the bicycle model, a fuzzy-logic controller, which is adaptive to the speed change is implemented to control the bicycle to follow the roll-angle commands. The controller parameters where fuzzy membership functions are presented by scaling factors and deforming coefficients are optimised using genetic algorithms. Results show that the bicycle can follow the roll-angle command with short time delay and the control structure can adapt to a wide range of speed.