The Dynamic Positioning (DP) system is responsible for the stationkeeping and manoeuvrability of a vessel in offshore operations. The forces required by the DP system are distributed among the available thrusters of the vessel by a thrust allocation algorithm, which should be both accurate — i.e. the sum of the effective forces is close to the required forces — and efficient — i.e. the total consumed power is minimal.

Ideally, the thrust allocation algorithm accounts for the forbidden zones, a practical solution to avoid significant hydrodynamic interaction effects such as thruster-hull interaction, thruster-current interaction and thruster-thruster interaction. Moreover, the thrust allocation algorithm should also take into account the physical limitations of each thruster such as the maximum thrust (saturation), the maximum rate of turn (azimuth) and the maximum rate of change of RPM.

In order to include these complex requirements in the thrust allocation algorithm the hydrodynamic interaction effects are modelled as efficiency functions, which are incorporated in the (power) object function and in the (required forces) constraints.

With the purpose of solving the complete problem, including the physical limitations and the hydrodynamic interaction effects, several advanced optimization methods were investigated. The selected optimization algorithms were the Sequential Quadratic Programming (SQP) method and the Steepest Descent (SD) method.

In this paper a DP drill ship is considered, with 6 azimuthing thrusters. Results were obtained for environmental conditions of increasing strength, from benign sea states to higher sea states with large required forces, eventually leading to thruster saturation. As a final test case, the required forces are such that the thrust allocation algorithm forces the thrusters to cross large forbidden zones with significant thruster-hull interaction.

The results show that the enhanced thrust allocation algorithm can deal with both hydrodynamic interaction effects and physical limitations in a time-efficient and robust manner. Altogether, these improvements are expected to lead to higher accuracy and efficiency for DP operations.

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