Finite-set Model Predictive Speed and Heading Control of Autonomous Surface Vehicles with Unmeasured States

This paper addresses the speed and heading control of under-actuated autonomous surface vehicles (ASVs) subject to model uncertainties and unmeasured states for performance improvement. At first, an extended state observer is developed for estimating unknown system uncertainties, external disturbances as well as unmeasured velocities of surge, sway and yaw. Then, a finite-set model predictive control method is utilized to achieve surge speed and heading stabilization in the presence of model uncertainties. The proposed predictive speed and heading control method is applied to straight-line path following of an ASV, and simulation results show the efficiency of the proposed predictive speed and heading controllers.