Physical parameter sensitivity of system eigenvalues and physical model reduction

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Date

2004-11

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Publisher

Pergamon-Elsevier Science

Abstract

The identification of subsystems and/or components that is related to a given eigenvalue of the overall system is a challenging and important topic. The use of special structure of the system matrices obtained busing bond graphs can result in identifying subsystems and/or components that affect a given eigenvalue of an overall system. This paper, by making use of a set of theorems and definitions proposes an efficient procedure for this purpose. The basic procedure is based upon the calculation of sensitivity of eigenvalues. The so-called "effect" matrices are produced that indicates the relative importance of physical parameters on a selected eigenvalue. In addition to the relative importance, the effect matrix is used for an efficient physical model reduction procedure. Furthermore, reasons of different dynamic behavior of a system can be explained. Use of effect matrices also improves the physical model reduction method based on decomposition procedures. Three examples are given to illustrate the approach and its consequences.

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Keywords

Automation and control systems, Engineering, Mathematics, Eigenvalue sensitivity, Physical parameters, Physical model reduction, Hankel singular values (HSV), Control systems, Eigenvalues and eigenfunctions, Mathematical models, Matrix algebra, Reduction, Sensitivity analysis, Large scale systems

Citation

Orbak, A. Y. vd. (2004). “Physical parameter sensitivity of system eigenvalues and physical model reduction”. Journal of the Franklin Institute-Engineering and Applied Mathematics, 341(7), 631-655.