Direct adaptive fuzzy-basis-function-network motion control for self-balancing two-wheeled transporters

This paper presents a direct adaptive motion control using fuzzy basis-function networks (FBFN) for a self-balancing two-wheeled transporter (SBTWT) with unknown parameters and uncertainties. With the decomposition of the overall system into two subsystems: yaw motion control and mobile inverted pendulum, two direct adaptive FBFN motion controllers are respectively proposed to achieve posture maintenance, speed following and yaw motion control. Asymptotic stabilities of the two controllers with their FBFN weighting updating rules are derived via the Lyapunov stability theory. Simulation results indicate that the proposed controllers are capable of providing satisfactory control actions to steer the vehicle.