A significant amount of work has been reported in the area of vision-based stabilization of wheeled robots during the last decade. However, almost all the contributions have not considered the actuator dynamics in the controller design. Considering the unknown parameters of the robot kinematics and dynamics incorporating the actuator dynamics, this paper presents a vision-based robust adaptive controller for the stabilization of a wheeled humanoid robot by using the adaptive backstepping approach. For the controller design, the idea of backstepping is used and the adaptive control technique is applied to treat all parametric uncertainties. Moreover, to attenuate the effect of the external disturbances on control performance, smooth robust compensators are employed. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, simulation results are given to verify the effectiveness of the proposed controller.
Robust Adaptive Control of Two Chaotic Systems with Unknown Parameters
