Abstract
One of the most important problems in dynamic systems theory is to approximate a higher-order system model with a low-order, relatively simpler model. However, the nominal high-order model is never an exact representation of the true physical system. In this paper the problem of approximating an uncertain high-order system with constant real parameter uncertainty by a robust reduced-order model is considered. A parameter-dependent quadratic bounding function is developed that bounds the effect of uncertain real parameters on the model-reduction error. An auxiliary minimization problem is formulated that minimizes an upper bound for the model-reduction error. The principal result is a necessary condition for solving the auxiliary minimization problem which effectively provides sufficient conditions for characterizing robust reduced-order models.
Original language | English (US) |
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Pages (from-to) | 248-253 |
Number of pages | 6 |
Journal | IEEE Transactions on Automatic Control |
Volume | 42 |
Issue number | 2 |
DOIs | |
State | Published - 1997 |
Keywords
- Real parameter uncertainty
- Reduced-order modeling
- Uncertain systems
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering