The Combined Methodology forReducing theHigh Model Order foraContinuous System Using Genetic AlgorithmandDominant Poles Methods
Journal Title: International Journal of Contemporary Research and Review - Year 2018, Vol 9, Issue 6
Abstract
Model order reduction is one of the crucial topics facing researchersnowadays. Various methods were conducted for achieving this goal. In this article, genetic algorithm (GA)with dominant polesmethodsareused to reduce high-order transfer functions (TFs) tolower-order ones. Genetic algorithm is powerful techniqueused foroptimization purposes. In this approach, genetic algorithm is applied to model order reduction to reduce the order of the numerator of TF whereas the dominant polesmethod is used to reduce the order of denominator of the TF and thus improvingaccuracy and preserving the same dominant poles for the reduced system asthe original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original high ordermodels being reduced
Authors and Affiliations
Mohammad A. ALMa’aitah
Keywords
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- EP ID EP546347
- DOI 10.15520/ijcrr/2018/9/06/531
- Views 73
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