Autonomous Underwater Vehicle Robust Path Tracking: Generalized Super-Twisting Algorithm and Block Backstepping Controllers

Abstract

This paper deals with the design and implementation of two nonlinear control strategies to solve the path-tracking problem for an Autonomous Underwater Vehicle (AUV) under model uncertainties and external disturbances. First, the AUV model is transformed into the so-called regular form by an appropriate selection of state variables. Afterward, the trajectory tracking problem is treated under two different perspectives; on the one hand, the Block Backstepping Control (BBSC) design was employed, in this methodology, the system into the regular form is rewritten regarding the error tracking dynamics and then the control law is obtained through a Lyapunov function stability analysis. The other method is based on the second order sliding mode technique known as Generalized Super-Twisting Algorithm (GSTA) which offers a way to ensure robustness to modeling errors and bounded external disturbances. Both control laws are designed to maintain a minimum margin of error in the trajectory tracking of the AUV even in the presence of damping and buoyancy disturbances. Finally, experimental results are also provided to illustrate the performances of the closed-loop system using proposed controllers.