Nonlinear nondynamic systems which can be modelled by a linear combination of nonlinear functions are considered. An algorithm, based on correlation techniques, is presented for reducing the number of terms in such a model to a fixed but arbitrary number, n. It is shown that when the model is a line
A fundamental theorem for the model reduction of nonlinear systems
โ Scribed by F. Mossayebi; T.T. Hartley; J.A. De Abreu-Garcia
- Publisher
- Elsevier Science
- Year
- 1992
- Tongue
- English
- Weight
- 451 KB
- Volume
- 329
- Category
- Article
- ISSN
- 0016-0032
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โฆ Synopsis
A simple, but fundamental, theorem is given on the extent to which a nonlinear system model can have its order reduced. EssentialIy, the result is that the order, or the dimension of the state space representation, cannot be reduced to, or below, the dimension of the system's attractor. Several examples are given to illustrate this point. The result is especially applicable to higher order systems such as the in$nite dimensional systems arising from the modeling of distributed parameter systems.
๐ SIMILAR VOLUMES
A new methodfor the model reduction of linear discrete stable systems in Z-transfer functions is presented. First, a set of parameters is defined, whose values uniquely determine the given system. Then an always stable reduced approximant is obtained by neglecting the parameters which do not contrib
## In this paper, a model reduction technique to remedy the singularity of reduced- order models is proposed. The approach adopted is based on the least-square fitting of timemoments of the system. The proposed method is also auailable to stabilize unstable reduced models. This method is superior t