Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system

Ahmad Azwan, Abdul Razak and Ahmad Nor Kasruddin, Nasir and Nurul Amira, Mhd Rizal and Nor Maniha, Abd Ghani and Mohd Falfazli, Mat Jusof and Mohd Ashraf, Ahmad (2022) Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system. In: Lecture Notes in Electrical Engineering; 12th National Technical Seminar on Unmanned System Technology, NUSYS 2020 , 24-25 November 2020 , Virtual, Online. 923- 935., 770 (266059). ISSN 1876-1100 ISBN 978-981162405-6

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DOI/Official URL: https://doi.org/10.1007/978-981-16-2406-3_69

Abstract

This paper presents an improved version of Manta Ray Foraging Optimization (MRFO). MRFO is relatively a single objective optimization algorithm. It was inspired from the behavior of a cartilaginous fish called Manta Ray. Manta Ray applies three strategies in searching foods which are chain, cyclone and somersault foraging. From the study, MRFO is a relatively new developed algorithm and has low convergence rate. However, MRFO has potential to be improved in that aspect. In the meanwhile, Opposition-based Learning (OBL) is a well-known technique in increasing the convergence rate. Therefore, a type of OBL namely Quasi Oppositional-based Learning will be adopted into MRFO in order to increase the possibility of finding the solution by considering the opposite individual location of fitness. This version of MRFO is called as Oppositional-based MRFO (OMRFO). Further, OMRFO was performed on several benchmark function. A statistical non-parametric Wilcoxon Test was conducted to analyze the accuracy of MRFO and OMRFO. Furthermore, the proposed algorithm was applied to an inverted pendulum system. Result from shows that performance of OMRFO is significantly outperformed MRFO after tested in the benchmark functions.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Accuracy; Convergence; Inverted pendulum; Manta ray; Optimization; PD-controller; Quasi-opposition-based learning; Single-objective; Spiral
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies College of Engineering Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	14 Dec 2023 02:07
Last Modified:	14 Dec 2023 02:07
URI:	http://umpir.ump.edu.my/id/eprint/39652
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