An optimal thrust allocation algorithm with bivariate thrust efficiency function considering hydrodynamic interactions

Thrust allocation is of great importance for the application of Dynamic Positioning System (DPS). For dynamically positioned vessels, the thrust allocation is formulated as a nonlinear optimization problem, where the demanded forces and moments are distributed among the available thrusters. Both hydrodynamic interaction effects and physical limitations of thrusters affect the thrust generation. Therefore, the thrust allocation algorithm can be improved if these effects are considered. We propose a bivariate thrust efficiency function, dealing with both the forward thruster angle and the rear thruster angle, to describe the thrust loss. The thrust efficiency function is obtained from the model tests and approximated by the Radial Basis Function (RBF) neural network. The consequent thrust allocation problem is solved by the Sequential Quadratic Programming (SQP) algorithm with slack variables. The numerical simulations demonstrate a maximum power reduction of 16.03% compared with the forbidden zone algorithm. The proposed algorithm can also enhance system stability, highlighting the advantages of taking bivariate thrust efficiency function into account.