Abstract
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 control-based 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 real-time results are generated. Note to Practitioners —Accurate dynamic positioning (DP) of vessels in the presence of environmental disturbances is very important for Arctic explorations. This paper proposes a tightly coupled approach to estimate the unknown forces acting on a vessel and the vessel states. Also, an optimum control-based solution is proposed for robust DP.
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