DEVELOPMENT OF AN ARTIFICIAL BEE COLONY BASED PROPORTIONAL-DERIVATIVE CONTROLLER FOR COURSE KEEPING IN TANKERSHIP

Abstract

This paper presents the control system development using Artificial Bee Colony
(ABC) algorithm based Proportional-Derivative (PD) controller for automatic
control of tanker ship steering system. Multi-purpose or automatic Navigation,
Control and Guidance (GNC) of ocean vehicles generally rotates around the course
changing and keeping manoeuvres. In order to stabilize or change a course, a very
good steering control performs an essential function in the whole GNC system.
Course changing and keeping manoeuvres requires efficient control algorithms that
is capable of changing the course vessel with a sudden and precise response, with
the aim of improving the efficiency of fuel, and a reduction wear on ship
components. The GNC uses a simple control algorithm like the PD controller. The
effect of the controller depends greatly to the choice of the designer on the control
gains (Kp and Kd). For variations that are high and unpredictable, the ship’s
controller parameters must be continually modified, since the ship’s parameter
differs with other parameters like trim, loading, speed, wind, current, waves, depth
and other ocean conditions. In this work, a developed control system for the course
keeping manoeuvre of the tanker ship was designed using an ABC tuned PD. The
performance of the developed controller was compared with existing work in
literature using MATLAB 2015b simulation environment, and the simulation tests
was carried out on the mathematical model of the tanker ship. To achieve reference
data for comparison, Genetic Algorithm (GA) and Ant Colony Optimization (ACO)
based controllers tested using the same conditions. The simulation result shows that
ABC based PD controller gave an improvement of 18.8% in rise time over GA based
controller, and also an improvement of 7.7% in rise time over ACO based controller
respectively.