Model order reduction method based on improved sine cosine algorithm

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...

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Bibliographic Details
Main Authors: Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2023
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/38256/1/Model_Order_Reduction_Method_based_on_Improved_Sine_Cosine_Algorithm.pdf
http://umpir.ump.edu.my/id/eprint/38256/7/Model%20order%20reduction%20method%20based%20on%20improved%20sine%20cosine%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/38256/
https://doi.org/10.1109/ICSPC55597.2022.10001773
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Summary: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.