Invasive weed optimization for model order reduction of linear MIMO systems

In this work, a model order reduction (MOR) technique for a linear multivariable system is proposed using invasive weed optimization (IWO). This technique is applied with the combined advantages of retaining the dominant poles and the error minimization. The state space matrices of the reduced order...

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Bibliographic Details
Published in:Applied mathematical modelling 2013-03, Vol.37 (6), p.4570-4577
Main Authors: Abu-Al-Nadi, Dia I., Alsmadi, Othman M.K., Abo-Hammour, Zaer S., Hawa, Mohammed F., Rahhal, Jamal S.
Format: Article
Language:English
Subjects:
Eigenvalues
Errors
Invasive weed optimization
Mathematical analysis
Mathematical models
MIMO systems
Model order reduction
Optimization
Order reduction
Weeds
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Summary:In this work, a model order reduction (MOR) technique for a linear multivariable system is proposed using invasive weed optimization (IWO). This technique is applied with the combined advantages of retaining the dominant poles and the error minimization. The state space matrices of the reduced order system are chosen such that the dominant eigenvalues of the full order system are unchanged. The other system parameters are chosen using the invasive weed optimization with objective function to minimize the mean squared errors between the outputs of the full order system and the outputs of the reduced order model when the inputs are unit step. The proposed algorithm has been applied successfully, a 10th order Multiple-Input–Multiple-Output (MIMO) linear model for a practical power system was reduced to a 3rd order and compared with recently published work.
ISSN:0307-904X
DOI:10.1016/j.apm.2012.09.006