Open AccessMODEL REFERENCE ADAPTIVE CONTROL-BASED GENETIC ALGORITHM DESIGN FOR HEADING SHIP MOTION
Author(s) -
Nasir Ahmed Alawad
Publication year - 2020
Publication title -
acta polytechnica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.207
H-Index - 15
eISSN - 1805-2363
pISSN - 1210-2709
DOI - 10.14311/ap.2020.60.0197
Subject(s) - heading (navigation) , control theory (sociology) , pid controller , linear quadratic regulator , genetic algorithm , matlab , controller (irrigation) , actuator , reference model , computer science , control engineering , engineering , control (management) , temperature control , artificial intelligence , agronomy , software engineering , machine learning , biology , aerospace engineering , operating system
In this paper, the heading control of a large ship is enhanced with a specific end goal, to check the unwanted impact of the waves on the actuator framework. The Nomoto model is investigated to describe the ship’s guiding progression. First and second order models are considered here. The viability of the models is examined based on the principal properties of the Nomoto model. Different controllers are proposed, these are Proportional Integral Derivative (PID), Linear Quadratic Regulator (LQR) and Model Reference Adaptive Control Genetic optimization Algorithm (MRAC-GA) for a ship heading control. The results show that the MRAC-GA controller provides the best results to satisfy the design requirements. The Matlab/Simulink tool is utilized to demonstrate the proposed arrangement in the control loop.