Dynamic Positioning of Vessels Using a UKF-Based Observer and an NMPC-Based Controller

This paper presents a solution to the problem of dynamic positioning (DP) of vessels in ice-infested environments using a nonlinear observer and a finite-horizon optimal controlbased approach. An unscented Kalman filter-based nonlinear observer is developed to estimate both the vessel states and the unknown inputs, such as the ice load. To perform better control and disturbance rejection, a nonlinear model predictive controller is employed for DP. The developed modules are integrated with a commercial vessel maneuvering software, and promising realtime results are generated.