High order state variable models of chemical processes can be reduced to lower order models by matching the moments of the impulse responses for those states which it is desired to retain. The moments of the full model are calculated directly from the state equations and the parameters of the reduce
The reduction of complex transfer function models to simple models using the method of moments
β Scribed by L.G. Gibilaro; F.P. Lees
- Publisher
- Elsevier Science
- Year
- 1969
- Tongue
- English
- Weight
- 580 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0009-2509
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β¦ Synopsis
Complex transfer function models of chemical plant can be reduced to simple models using the method of moments. Two such simple transfer function models are and G(s) = exp [-,sl (1+7qS)(1+T3S) G(s) = exp 1~~~1 (1+7*s)"' The three parameters of the simple model are obtained by matching the first three moments of the impulse response of the complex and simple models.
π SIMILAR VOLUMES
The parameters of simple transfer function models of chemical processes can be obtained from the state variable models usually derived by matching the moments of the impulse response of the two models. It has been shown previously how the moments of the state variable model may be derived directly f
## Abstract __In vitro__ and __in vivo__ techniques have been utilized to estimate mass transfer coefficients for physiological pharmacokinetic models. No single method has been adopted for estimating this parameter, in part, due to the different model structures with which this parameter may be as
In this paper, the reduction method uses the concepts of stability-equation and important poles to find the denominator of the reduced model. Then the numerator of the reduced model is found by complex curve fitting. This method tends to simultaneously guarantee a stable reduced model from a stable
## Abstract A stochastic method of optimization, which combines simulated annealing with simplex, is implemented to fit the parameters of a simple model potential. The main characteristic of the method is that it explores the whole space of the parameters of the model potential, and therefore it is