Model reduction for state-space symmetric systems
β Scribed by W.Q. Liu; V. Sreeram; K.L. Teo
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 96 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0167-6911
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β¦ Synopsis
In this paper, the model reduction problem for state-space symmetric systems is investigated. First, it is shown that several model reduction methods, such as balanced truncation, balanced truncation which preserves the DC gain, optimal and suboptimal Hankel norm approximations, inherit the state-space symmetric property. Furthermore, for single input and single output (SISO) state-space symmetric systems, we prove that the H β norm of its transfer functions can be calculated via two simple formulas. Moreover, the SISO state-space symmetric systems are equivalent to systems with zeros interlacing the poles (ZIP) under mild conditions.
π SIMILAR VOLUMES
The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject