Dual Coefficient Passivity-Based Sliding Mode Control for Robust Path Following of Autonomous Marine Vehicles With Simulations and Experiments

Robust path-following is a key requirement for Autonomous marine vehicles (AMVs) operating under external disturbances and model uncertainty. This article proposes a dual-coefficient passivity-based sliding mode control (PBSMC) scheme that secures finite-time convergence while substantially simplifying the control architecture. Conventional AMV dynamics are formulated within a Hamiltonian framework, enabling rigorous stability analysis without detailed structural assumptions. Notably, the PBSMC algorithm utilizes only two control coefficients, thereby simplifying the control architecture and enhancing reliability. Extensive simulations covering three paths and five test cases confirm superior path following performance, with the mean absolute error (MAE) and root-mean-square error (RMSE) bounded by 0.3745 and 1.1736 m, respectively. Compared with classical sliding mode, backstepping, and adaptive fuzzy sliding mode controllers, the PBSMC algorithm records the highest accuracy (MAE = 0.2490 m; RMSE = 1.0018 m). Lake trials on the NGC4MR-AUV1.0 platform further confirm practical applicability: the vehicle maintains precise waypoint following under environmental disturbances and rapidly recovers from abrupt disruptions. These results indicate that the dual-coefficient PBSMC scheme offers a reliable, readily implementable solution for high-precision AMV path following for real-world applications.