Resilient adaptive trajectory tracking control for uncalibrated visual servoing systems with unknown actuator failures

Abstract

A resilient adaptive tracking control scheme for uncalibrated visual servoing system with unknown actuator failures is proposed, where the camera parameters, the robotic physical parameters, and the position information of end-effector cannot be measured accurately. For our scheme, the nonlinear composite Jacobian matrix involving unknown parameters is estimated by an adaptive algorithm based on the depth-independent interaction matrix frame so that the image feature with time-varying depth can be tackled effectively. With the use of projection technique in the adaptive algorithm, the possible singularity of the estimated composite Jacobian matrix can be well circumvented without any stringent assumption, which is critical for establishing the closed-loop stability. Moreover, a novel adaptive resilient control scheme based on dynamic decoupling is developed to separate the design of visual servoing controller and fault compensation, improving the visual servoing system resilience against unknown actuator failures in uncalibrated environment. Through a rigorous Lyapunov argument, the asymptotic convergence of image tracking error to zero is established successfully regardless of the occurrence of unknown actuator failures. The effectiveness of the proposed visual tracking control scheme is confirmed by simulation results.