Image-based visual tracking adaptive control for mobile robots

In this paper, we deal with the problem of image-based visual tracking for mobile robots. It is noted that the presence of actuator dynamics and the unknown target motion increases the complexity of the system model and makes the design of the controller more difficult. To solve this problem, we propose an adaptive control approach via utilizing backstepping technique and extended state observer (ESO). For the controller design, the adaptive technique is employed to estimate the bound of the target motion and the adaptive law is derived from the Lyapunov stability theory. We also adopt two ESOs to estimate and compensate for the disturbances affecting the mobile robot dynamics and the wheel actuator dynamics. It is shown that the proposed adaptive controller guarantees the boundness of all the signals in the closed-loop system and enables the tracking errors to exponentially converge to a compact set which is adjustable.