Experimental Assessment of a Cascaded Path-Following Controller for ASVs Using Extended State Estimation

This work presents a cascaded control strategy for underactuated autonomous surface vehicles, integrating an extended state estimator within a path-following controller. Although path-following control has been extensively addressed in the literature, its experimental implementation continues to face significant challenges, particularly in real-world environments characterized by dynamic uncertainties, unmodeled disturbances, and measurement noise. The proposed architecture preserves the classical structure of cascade control, applying a surge-guided line-of-sight-based guidance law at the kinematic layer and a modified robust-adaptive backstepping controller at the dynamic layer. Both controllers take advantage of a nonlinear set-membership extended state observer, reformulated to incorporate a recently identified kinetic model that accounts for uncertainties in both the inertial dynamics and the propulsion system. The main contributions of this work include the reformulation of the observer to incorporate the identified model and the integration of angular velocity measurements, as well as the demonstration of the input-to-state stability of the low-level tracking errors with respect to estimation errors. Another significant contribution is the experimental validation of the complete strategy on a catamaran-type autonomous surface vehicle, operating under real-world conditions with unmeasured disturbances. The experimental results demonstrate robust and accurate performance in both estimation and control across various circuit exercises.