Adaptive Trajectory Tracking Error Constraint Control of Unmanned Underwater Vehicle Based on a Fully Actuated System Approach

This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles (UUVs) with unknown dead-zone inputs. The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems (FAs) approach to enable UUVs to asymptotically track target signals. Firstly, a novel error constraint fully actuated systems (ECFAs) approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling. Secondly, in order to deal with the model uncertainties of the UUVs, adaptive radial basis function neural networks (RBFNNs) is combined with the ECFAs approach. Then, a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs, and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions. Finally, the simulation results demonstrate the effectiveness of the designed adaptive controller.