Author(s)

R.S. Burns, R. Richter & M.N. Polkinghorne

Abstract

Conventional techniques to model plants require the utilisation of differential equations. The computation of such equations becomes slow in situations when the plants are highly complex. By taking training data from the real plant, it is possible to design and train a neural network which is capable of achieving a successful plant model using an off-line backpropagation technique. For a marine application, analysis of the results of this study is included which demonstrates how this technique may be applied, and the nature of the performance obtainable. 1 Introduction The classical approach to modelling the dynamic behaviour of rigid bodies is to express their behaviour as a set

Keywords