Composite adaptive-based trajectory tracking for unmanned surface vessels under unknown dynamics parameters

To address the trajectory tracking problem of unmanned surface vessels (USVs) when all dynamics parameters are unknown. This study designs a trajectory tracking controller for USVs based on Lyapunov theory and composite adaptive control technology. And based on dual feedback signals from tracking error and forecast error, an adaptive update law for dynamics parameters is designed using the Bounded Gain Forgetting Least Squares method. The adaptive update law enables the online identification of all dynamics parameters of USVs. Next, a concise nonlinear disturbance observer is designed based on error feedback signals to compensate for unknown time-varying environmental disturbances. A control law incorporating dynamics parameters adaptive update law and disturbance estimation is developed using composite adaptive control techniques. Subsequently, the convergence of trajectory tracking errors and dynamics parameters estimation errors is proven based on Lyapunov theory. Finally, numerical simulation experiments are conducted. The results of simulation experiments demonstrate that the proposed controller achieves precise trajectory tracking for the USV even when all dynamics parameters are completely unknown. Additionally, the controller exhibits robust disturbance rejection capabilities.