Soft Computing

, Volume 22, Issue 10, pp 3449–3459 | Cite as

Reduced order modelling of linear time-invariant system using modified cuckoo search algorithm

Methodologies and Application

Abstract

In this paper modified cuckoo search (MCS) algorithm is considered to develop reduced order model (ROM) of higher-order linear time-invariant systems. Firstly, the MCS algorithm has been employed to minimize the integral square error (ISE) between original and proposed ROM to obtain its unknown coefficients. Five systems of different order are considered to obtain their reduced order model. Finally, various performance indices, such as ISE, integral of absolute and integral of time multiplied by absolute error, have been estimated to reveal the efficacy of the proposed model. Also, time and frequency response characteristics of original higher-order model are compared with the proposed MCS-based and some of other existing techniques-based ROM available in the literature. Furthermore, the results are compared in terms of time response specifications such as rise time (\(t_\mathrm{r} \)) in second, settling time (\( t_\mathrm{s}\)) in second and maximum peak overshoot (\( M_\mathrm{p}\)) in percentage. It is revealed that the response of the proposed MCS-based ROM is much closer to the response of the original higher-order system.

Keywords

Modified cuckoo search algorithm Optimization Order reduction Integral square error 

Notes

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of Electrical EngineeringGraphic Era UniversityDehradunIndia

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