Design of three exponentially convergent robust controllers for the trajectory tracking of autonomous underwater vehicles

This paper deals with the trajectory tracking problem of autonomous underwater vehicles (AUVs) in the presence of dynamic uncertainties and time-varying external disturbances. Three exponentially convergent robust controllers, namely, the min-max type controller, the saturation type controller and the smooth transition type controller are proposed to drive an AUV to track a predefined trajectory. It is shown that the filtered tracking errors, position tracking errors and velocity tracking errors for the three proposed controllers are exponentially convergent. Moreover, all the above tracking errors for the three proposed controllers can be shaped by specific analytic expressions and such expressions illustrate how the transient responses of the above tracking errors can be modified by adjusting the control parameters. The characteristics of the three proposed controllers are summarized and demonstrated with numerical simulations. Theoretical comparison analysis and comparative simulations with the existing RISE-based controller of AUV are presented to show the effectiveness of the three proposed exponentially convergent robust controllers.