Disturbance-compensated NMPC control for cooperative path following of USV-UAVs formation

Abstract

This paper proposes a novel nonlinear model predictive control (NMPC) strategy for cooperative path following of unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs) formation, enhanced by a nonlinear disturbance observer (NDOB) to address external disturbances and model uncertainties. Accurate mathematical models of USV and UAV dynamics under perturbations are established, and a discretized predictive model is formulated to efficiently solve the constrained open-loop optimization problem. Stability analysis of both the controller and observer is conducted using Lyapunov theory. Simulation results demonstrate that the proposed method achieves precise formation path following, with significant improvements in tracking performance compared to classical MPC controllers. Specifically, reductions of 57.41%, 57.58%, and 45.65% are observed in the indexes of integral absolute error (IAE), mean absolute error (MAE), and root mean square error (RMSE), respectively. This approach provides a promising solution for coordinated multi-vehicle control in maritime operations and similar applications.