Neural Networks Based Analysis of Ship Roll Stabilization

Abstract

This paper presents a neural network (NN) controller which is one of the active control methods for a container ship roll stabilizer system. The aim of this study is to constitute neural network controller which uses fins to reduce roll amplitude. During the control operation, the control signal error is used with back-propagation algorithm to update the weights of the neural controller. The obtained results have been compared with the uncontrolled simulation results. The simulation results showed that the performances of controllers are excellent.