Key points are not available for this paper at this time.
This paper investigates a trajectory tracking control method for multi-underactuated underwater vehicle (AUV) formations with uncertain model parameters and external environmental disturbances. Firstly, a dual closed-loop fixed-time integral sliding mode controller is designed. By combining fixed-time theory and integral sliding mode control, this controller ensures the stability of the formation tracking and guarantees the convergence of the tracking error to zero within a fixed time duration. Secondly, an adaptive radial basis function (RBF) neural network controller is integrated with a conditional integrator to address uncertainties in model parameters, approximation errors, and external environmental disturbances in practical multi-AUV systems. This controller exhibits robustness and adaptivity. Additionally, a virtual leader strategy is employed to enhance the robustness of the formation system and prevent formation collapse caused by leader AUV failures. Finally, simulation results validate the effectiveness of the proposed formation controller, demonstrating accurate trajectory tracking by the AUV formation.
Zhang et al. (Sat,) studied this question.