Efficient ship track keeping using predictive PID controller

Abstract

Present day’s unmanned surface vehicles are important where human cannot enter. Navigating these unmanned vehicles plays an important role. This work is proposed with an efficient navigation of unmanned vehicle using predictive proportional-integral-derivative (PID) variants controller. Many researchers are working on the ship track keeping efficiency. This work is an attempt made to reach the maximum efficiency in track keeping. PID controllers are very simple but only PID controller is less efficient compare to predictive and fuzzy controller. Fuzzy and neural network based controller complex in nature. The adaptive controllers are also used to keep the ship on track, but the adaptive controller also complex and sometimes fail to maintain the maximum efficiency. Predictive neural, predictive fuzzy also can be used but again complex. Keeping these limitations in mind an efficient ship track keeping using predictive PID variants is developed which is simple compare to predictive fuzzy and predictive neural and efficiency achieved is around 99.98% and this efficiency is compared with simple PID variants controllers.