Tuning Factor the Single Input Fuzzy Logic Controller to Improve the Performances of Depth Control for Underwater Remotely Operated Vehicle

Abstract

This paper investigates the factor of tuning variable parameter for Single Input Fuzzy Logic Controller (SIFLC) to improve the performances of depth control for the underwater Remotely Operated Vehicle (ROV). This study and investigates will focus on the number of rules in SIFLC, lookup table, slope of a linear equation, and also model reference to give optimum performances of depth control without overshoot in system response and faster rise time and settling time. The variable parameter for SIFLC is tuned by Particle Swarm Optimization (PSO) algorithm. The investigation focused on the number of rules will be reduced, SIFLC parameter reduced, represented lookup table as a linear control surface method to represent the inference engine of FLC. The investigation on model reference also covered in this paper. The current of model reference will give the best system response for depth control. The slope of linear equation either in positive and negative values and come up from conventional FLC then will simplify into SIFLC. The results obtained the number of rules, the slope of linear equations and model reference will be affecting the results of system performances.