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ThinkMind // ICAS 2011, The Seventh International Conference on Autonomic and Autonomous Systems // View article icas_2011_3_40_20053


Reduced Order Modeling of Linear MIMO Systems Using Particle Swarm Optimization

Authors:
Dia Abu-Al-Nadi
Othman Alsmadi
Zaer Abo-Hammour

Keywords: Model Order Reduction;MIMO Systems;Particle Swarm Optimization.

Abstract:
In this work, a model order reduction (MOR) technique for a linear multivariable system is proposed using the combined advantage of retaining the dominant poles and the error minimization using the particle swarm optimization. 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 particle swarm 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 4th order and an 8th order Single-Input-Single-Output (SISO) system was reduced to a 2nd order.

Pages: 62 to 66

Copyright: Copyright (c) IARIA, 2011

Publication date: May 22, 2011

Published in: conference

ISSN: 2308-3913

ISBN: 978-1-61208-134-2

Location: Venice/Mestre, Italy

Dates: from May 22, 2011 to May 27, 2011

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