Publication detail

Reduced order infinite impulse response system identification using manta ray foraging optimization

MAHATA, S. HERENCSÁR, N. ALAGOZ, B.B. YEROGLU, C.

Original Title

Reduced order infinite impulse response system identification using manta ray foraging optimization

Type

journal article in Web of Science

Language

English

Original Abstract

This article presents a useful application of the Manta Ray Foraging Optimization (MRFO) algorithm for solving the adaptive infinite impulse response (IIR) system identification problem. The effectiveness of the proposed technique is validated on four benchmark IIR models for reduced order system identification. The stability of the proposed estimated IIR system is assured by incorporating a pole-finding and initialization routine in the search procedure of the MRFO algorithm and this algorithmic modification contributes to the MRFO algorithm when seeking stable IIR filter solutions. The absence of such a scheme, which is primarily the case with the majority of the recently published literature, may lead to the generation of an unstable IIR filter for unknown real-world instances (particularly when the estimation order increases). Experiments conducted in this study highlight that the proposed technique helps to achieve a stable filter even though large bounds for the design variables are considered. The convergence rate, robustness, and computational speed of MRFO for all the considered problems are investigated. The influence of the control parameters of MRFO on the design performances is evaluated to gain insight into the interaction between the three foraging strategies of the algorithm. Extensive statistical performance analyses employing various non-parametric hypothesis tests concerning the design consistency and convergence are conducted for comparison of the proposed MRFO-based approach with six other metaheuristic search procedures to investigate the efficiency. The results on the mean square error metric also highlight the improved solution quality of the proposed approach compared to the various techniques published in the literature.

Keywords

Infinite impulse response system; Manta ray foraging optimization; Mean square error; Metaheuristics; Non-parametric statistical tests; System identification

Authors

MAHATA, S.; HERENCSÁR, N.; ALAGOZ, B.B.; YEROGLU, C.

Released

5. 1. 2024

Publisher

Elsevier

ISBN

2090-2670

Periodical

Alexandria Engineering Journal

Year of study

87

Number

1

State

Arab Republic of Egypt

Pages from

448

Pages to

477

Pages count

30

URL

https://www.sciencedirect.com/science/article/pii/S1110016823011468

Full text in the Digital Library

http://hdl.handle.net/11012/244197

BibTex

@article{BUT186919,
  author="Shibendu {Mahata} and Norbert {Herencsár} and Baris Baykant {Alagoz} and Celaleddin {Yeroglu}",
  title="Reduced order infinite impulse response system identification using manta ray foraging optimization",
  journal="Alexandria Engineering Journal",
  year="2024",
  volume="87",
  number="1",
  pages="448--477",
  doi="10.1016/j.aej.2023.12.054",
  issn="2090-2670",
  url="https://www.sciencedirect.com/science/article/pii/S1110016823011468"
}