Nonlinear model predictive control-based guidance law for path following of unmanned surface vehicles

This work proposes a nonlinear model predictive control-based guidance strategy for unmanned surface vehicles, focused on path following. The application of this strategy, in addition to overcome drawbacks of previous line-of-sight-based guidance laws, intends to enable the application of predictive strategies also to the low-level control, responsible for tracking the references provided by the guidance strategy. The stability and robustness of the proposed strategy are theoretically discussed. Furthermore, given the non-negligible computational cost of such nonlinear predictive guidance strategy, a practical nonlinear model predictive control strategy is also applied in order to reduce the computational cost to a great extent. The effectiveness and advantages of both proposed strategies over other nonlinear guidance laws are illustrated through a complete set of simulations. • A nonlinear model predictive control-based guidance strategy for USVs is proposed. • The robustness and stability of the proposed strategy are theoretically shown. • A practical predictive strategy is also applied to reduce the computational cost. • Simulations show the effectiveness of the proposed strategies over existing laws.