Model order reduction method based on improved sine cosine algorithm

Mohd Zaidi, Mohd Tumari and Mohd Ashraf, Ahmad and Mohd Helmi, Suid and Mohd Riduwan, Ghazali (2023) Model order reduction method based on improved sine cosine algorithm. In: 10th IEEE Conference on Systems, Process and Control, ICSPC 2022 , 17 December 2022 , Melaka, Malaysia. pp. 155-159.. ISBN 978-1-6654-7098-8

	Pdf Model_Order_Reduction_Method_based_on_Improved_Sine_Cosine_Algorithm.pdf Restricted to Repository staff only Download (1MB) | Request a copy
Preview	Pdf Model order reduction method based on improved sine cosine algorithm.pdf Download (153kB) | Preview

Abstract

This paper presents an improved sine cosine algorithm (iSCA) for the reduction of high-order single-input single-output (SISO) systems. The proposed iSCA is adopted to solve the imbalance portion of the exploration and exploitation stages in the standard sine cosine algorithm (SCA). Specifically, a nonlinear decreasing updated gain is adopted to provide a proper balance of exploration and exploitation stages. The proposed iSCA is expected to yield a most accurate reduced-order model for a particular original high-order system by minimizing the integral square error (ISE) between their system output responses. The effectiveness of the proposed technique is evaluated by reducing a 6 th order double pendulum overhead crane model. The obtained simulation results revealed that the proposed iSCA is highly effective and remarkably consistent in obtaining an ideal reduced-order model compared to its original version.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Improved sine cosine algorithm (iSCA); Meta-heuristics algorithm; Model order reduction
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Dr Mohd Ashraf Ahmad
Date Deposited:	09 Aug 2023 08:09
Last Modified:	09 Aug 2023 08:09
URI:	http://umpir.ump.edu.my/id/eprint/38256
Download Statistic:	View Download Statistics

Actions (login required)

View Item