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A Practical Model Reduction Method for Complex Variable Identified System

[+] Author Affiliations
Jae Hyeuk Suk

Green River Community College, Auburn, WA

Brian C. Fabien

University of Washington, Seattle, WA

Paper No. IMECE2010-39697, pp. 473-481; 9 pages
doi:10.1115/IMECE2010-39697
From:
  • ASME 2010 International Mechanical Engineering Congress and Exposition
  • Volume 8: Dynamic Systems and Control, Parts A and B
  • Vancouver, British Columbia, Canada, November 12–18, 2010
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4445-8
  • Copyright © 2010 by ASME

abstract

This paper presents a practical model order reduction method which can handle the complex variable state-space model. The proposed model reduction method is based upon an identified result which is from the Eigensystem Realization Algorithm (ERA) with a complex variable transformation (z = x + iy) in [1]. The biggest advantage of a complex variable transformation is the fact that transformation (i) eliminates skew-symmetric term in state-space model and (ii) reduces a number of system states. However, using the complex variable transformation causes the result that an identified system includes the complex variables. Therefore, a new model reduction method for a complex variables state-space model is required. In particular, it is shown results of selecting system order with experimental data of flywheel energy storage system and the proposed method. Finally, a comparison of system order which is chosen by the other model reduction methods is analyzed.

Copyright © 2010 by ASME

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