Adaptive dynamic surface control for vision-based stabilization of an uncertain electrically driven nonholonomic mobile robot

This paper investigates the vision-based pose stabilization of an electrically driven nonholonomic mobile robot with parametric uncertainties in robot kinematics, robot dynamics, and actuator dynamics. A robust adaptive visual stabilizing controller is proposed with the utilization of adaptive control, backstepping, and dynamic surface control techniques. For the controller design, the idea of backstepping is used and the adaptive control approach is adopted to deal with all uncertainties. We also apply the dynamic surface control method to avoid the repeated differentiations of virtual controllers existing in the backstepping design procedure such that the control development is easier to be implemented. Moreover, to attenuate the effect of disturbances on control performance, smooth robust compensators are exploited. It is proved that all signals in the closed-loop system can be guaranteed to be uniformly ultimately bounded. Finally, simulation results are presented to illustrate the performance of the proposed controller.