Abstract
Dynamic Positioning System (DPS) can automatically control the position and motion path of a floating vessel subjected to environmental and external forces using the actuators, which is composed of several algorithms, such as controller, filters and optimal control allocation. The control allocation plays an important role for the performance of DPS. The purpose of the control allocation system is to distribute among the thrusters the desired generalized forces computed by the motion controller. The output from the control allocation is the desired thruster forces and directions. The control allocation problem is posed as a constrained quadratic program. This paper is concerned with neural network for solving dynamic convex quadratic programming problems with constraints, where the objective of the thruster is to give the desired forces and the cost function is used to determine the solution with the lowest power. In order to validate the effectiveness of the control allocation, a model experiment was carried out under the action of wind, current and waves. The experimental results show that the optimal algorithm of control allocation is very efficient.
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