Performance Evaluation of Artificial Bee Colony Based Proportional-Integral-Derivative Cascade Control System for Tanker Ship

Usman M. G., Shaaban Y. A., Adedokun E. A., Ajayi O., Abdulwahab I., Umar A.

Abstract


This paper presents the development of a cascade control system using an artificial bee colony based proportional-integral-derivative (PID) controller for automatic control of tanker ship steering system. Multi-purpose or automatic guidance, navigation and control (GNC) of ocean vehicles generally revolves around course keeping and course changing manoeuvres. In order to maintain or change a course, an efficient steering control plays an important role in the entire GNC system. Course keeping and course changing manoeuvres require efficient control algorithms capable of altering the course of the vessel with rapid and accurate response and with the hope of improving fuel efficiency and reducing wear on ship components. The GNC system often utilizes simple control algorithms such as the PID controller. The performance of the PID controller depends largely on the choice of its control gains (Kp, Ki and Kd). For large and unpredictable variations, the parameters of the ship’s controller must be continually modified since the dynamics of the ship vary with other parameters such as speed, loading, trim, wind, waves, current, depth and other ocean conditions. In this work, a cascade control system was developed for the course keeping and course changing manoeuvres. Both the inner loop and outer loop were designed with an ABC tuned proportional, integral and derivative (PID) controllers to control the ship’s course keeping and course changing. The performance of the developed controller was checked in simulation tests performed on the mathematical model of the tanker ship. To obtain reference data for comparison, genetic algorithm (GA) and ant colony optimization (ACO) based controllers were examined for the same conditions. For course keeping, the ABC based PD controller produced an improvement of 18.8% in rise time over GA based controller, and 7.7% in rise time over ACO based controller while for course changing the ABC based PD controller produced an improvement of 11.1% in rise time over GA based controller, and 13.6% in rise time over ACO based controller. The simulation was carried out using MATLAB R2015b. 

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References


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