Design of Constraints for a Neural Network based Thrust Allocator for Dynamic Ship Positioning

Abstract

Thrust allocation (TA) is an important component in dynamic positioning (DP) system of marine vessels. It plays a crucial role in offering power optimisation while meeting physical constraints of actuators in the vessel. Non-linear objective functions in TA formulation poses challenge to deriving the solution of TA schemes. While numerical optimisation techniques have tried to offer solution, the ability of neural network to model non-linearity offers a good technique of solving it. In this paper, design of constraints for TA scheme based on neural network is discussed. The allocator is based on a multi-layered autoencoder network. The allocator thus formulated is tested in various environmental and operational profiles against a numerical optimisation scheme to test its effectiveness in meeting the constraints.