Title: A novel method based on pole clustering technique and differential evolution for model order reduction

Authors: Shilpi Lavania; Deepak Nagaria

Addresses: Faculty of Electronics Engineering, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India ' Department of Electronics and Communication Engineering, Bundelkhand Institute of Engineering and Technology, Jhansi, Uttar Pradesh, India

Abstract: This paper strives to present a model order reduction (MOR) method for complex high order linear time-invariant (LTI) single input-single output (SISO) systems. The recommended method utilises the benefits of pole clustering method and differential evolution algorithm. In this suggested method, approximated denominator polynomial is obtained by pole clustering method whereas; approximated numerator is obtained using differential evolution algorithm. To indicate the effectiveness of the suggested method over existing MOR techniques, a comparison on the basis of a performance index known as integral square error (ISE) is depicted in this paper by using simulation graphs and in tabular form. Further, the suggested method is extended for MIMO systems also. Numerical examples are solved to give better understanding of the propound technique for SISO and MIMO systems. The recommended method derives and guarantees a stable approximated ROM if the original higher order system (HOS) is stable.

Keywords: model order reduction; MOR; single input single output systems; SISO; integral square error; ISE; pole clustering; differential evolution; performance index; PI.

DOI: 10.1504/IJCCIA.2020.105534

International Journal of Computational Complexity and Intelligent Algorithms, 2020 Vol.1 No.3, pp.215 - 230

Received: 14 Jan 2018
Accepted: 27 Sep 2018
Published online: 03 Mar 2020 *

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