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Neural Computing and Applications

, Volume 31, Issue 10, pp 6207–6221 | Cite as

A novel hybrid metaheuristic algorithm for model order reduction in the delta domain: a unified approach

  • Souvik GanguliEmail author
  • Gagandeep Kaur
  • Prasanta Sarkar
Original Article
First Online:

Abstract

Delta operator parameterization provides a unified framework in modeling, analysis and design of discrete-time systems, in which the resultant model converges to its continuous-time counterpart at high sampling limit. Capitalizing this unique property of delta operator, a new hybrid algorithm combining gray wolf optimizer and firefly algorithm has been proposed for model order reduction of high-dimensional linear discrete-time system. It has been shown that the reduced discrete-time model inherits all the dominant characteristics of the higher-order discrete-time model and with the increase in sampling frequency it converges to the continuous-time reduced model. The effectiveness of the proposed method is illustrated with the help of an example.

Keywords

Model order reduction (MOR) Pseudo random binary sequence (PRBS) Delta operator modeling Hybrid gray wolf optimizer (HGWO) 

Abbreviations

ABC

Artificial bee colony

bGWO

Binary gray wolf optimizer

DE

Differential evolution

EPDGWO

Evolutionary population dynamics gray wolf optimizer

FA

Firefly algorithm

GA

Genetic algorithms

GWO

Gray wolf optimizer

HS

Harmony search

HGWO

Hybrid gray wolf optimizer

IAE

Integral of absolute error

ITAE

Integral of time weighted absolute error

ISE

Integral of square error

ITSE

Integral of time weighted square error

IWO

Invasive weed optimization

PRBS

Pseudo random binary sequence

PSO

Particle swarm optimization

MEMS

Micro-electro-mechanical system

MIMO

Multi-input multi-output

MOR

Model order reduction

SISO

Single-input single-output

SSE

Sum of square error

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Department of Electrical and Instrumentation EngineeringThapar Institute of Engineering and TechnologyPatialaIndia
  2. 2.Department of Electrical EngineeringNational Institute of Technical Teachers’ Training and ResearchKolkataIndia

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