Non-dominated sorting manta ray foraging algorithm with an application to optimize PD control

Abdul Razak, Ahmad Azwan and Nasir, Ahmad Nor Kasruddin and Abd Ghani, N. M. and Mohammad, Shuhairie and Mat Jusof, Mohd Falfazli and Mhd Rizal, Nurul Amira (2022) Non-dominated sorting manta ray foraging algorithm with an application to optimize PD control. In: Lecture Notes in Electrical Engineering; Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2020 , 6 August 2020 , Gambang, Kuantan. 463 -474., 730. ISSN 1876-1100 ISBN 978-981334596-6

[img]
Preview
Pdf
Non-dominated sorting manta ray foraging algorithm .pdf

Download (149kB) | Preview
[img] Pdf
Non-dominated sorting manta ray foraging algorithm_FULL.pdf
Restricted to Repository staff only

Download (579kB) | Request a copy

Abstract

This paper presents a multi-objective (MO) version of Manta Ray Foraging Algorithm (MRFO) by using components in Non-Dominated Sorting Genetic Algorithm (NSGAII). MFRO is a recent developed algorithm which was inspired from behavior of a cartilaginous fish called Manta Ray. MRFO search solution by using three strategies of manta ray which are chain foraging, cyclone foraging and somersault foraging. However, this algorithm solves only single-objective problem and can be improved to solve multi-objective problem. Thus, non-dominated sorting (NS) strategies including crowding distance (CD) were adopted into MRFO. NS is a sorting technique based on Pareto’s game. It is a fast strategy to develop a good characteristic of Pareto’s front (PF). Meanwhile, CD is a strategy to preserve good distribution of solutions along the PF. This proposed algorithm is called NSMRFO. It is tested using several benchmark functions and its performance is compared to its parent by using statically analysis of hypervolume indicator. Then, it is applied to a Proportional-Derivative (PD)-controller for an Inverted Pendulum System (IPS) in order to know its performance on real-world application. Result of the NSMRFO on benchmark functions shows that it outperforms NSGAII and satisfactorily optimizes PD-control for the IPS.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Genetic algorithm; Manta ray foraging algorithm; Multi-objective algorithm; NSGAII; PD-Controller; Spiral
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Institute of Postgraduate Studies
Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 27 Sep 2022 02:31
Last Modified: 27 Sep 2022 02:31
URI: http://umpir.ump.edu.my/id/eprint/35293
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item