Performance analysis of a backpropagation neural controller system for a double-propeller boat model

摘要

This paper aims to analyze the performance of Backpropagation (BPNN)-controller system for an autonomous double-propeller boat model in terms of its settling time, in addition to the commonly analyzed control error. It is found that for a direct inverse neural controller system, the control error is highly affected by the required settling time, where most of the control errors are observed at the beginning of the control process.