A double-loop control framework for AUV trajectory tracking under model parameters uncertainties and time-varying currents. (1st December 2022) - Zhang, Zhuoyu; Lin, Mingwei; Li, Dejun
Abstract: Three-dimensional (3D) trajectory tracking of the underactuated autonomous underwater vehicle (AUV) is a challenging task due to the coupled nonlinear system dynamics, imprecise model parameters and time-varying currents. First, a double-loop framework incorporating the backstepping strategy is developed to decouple the tracking error for position into tracking error for controllable orientation. Second, three adaptive robust control (ARC) strategies are generated using desired compensation ARC, indirect ARC and direct/indirect ARC as controllers in the framework, respectively. Among these three strategies, two parameter adaptation laws are used to deal with the uncertainty of the model parameters, based on desired regressor and physical model, respectively. In addition, the three control strategies under this framework also show strong robustness to unknown time-varying ocean currents. Finally, the stability analysis and numerical simulation are presented. Under the numerical simulation of imprecise model parameters and unknown ocean currents, the transient and stable tracking performance of the three proposed control strategies is demonstrated. Highlights: Three adaptive robust control strategies are proposed using the double-loop framework for the trajectory tracking of AUVs. The control strategies improve the tracking accuracy compared with the strategy combined by virtual vehicle and PID-SMC. The transient and stable tracking performance of the proposed control strategies is demonstrated by simulation.