Trajectory tracking nonlinear model predictive control for autonomous surface craft

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This paper describes a solution to the problem of trajectory tracking control of autonomous surface craft (ASC) in the presence of constant ocean currents. The solution proposed is rooted in nonlinear model predictive control (MPC) techniques and addresses explicitly state and input constraints. Whereas state saturation constraints are added to the underlying optimization cost functional as penalties, input saturation constraints are made intrinsic to the nonlinear model used in the optimization problem, therefore reducing the computational burden of the resulting MPC algorithm. Simulation results obtained with a nonlinear dynamic model of a prototype ASC show that the MPC strategy adopted yields good performance in the presence of constant currents and holds good potential for real-time implementation.