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A new on-line parameter estimation strategy for fixed-bed reactors

✍ Scribed by Liang-Hong Liu; Xing-Gui Zhou; Wei-Kang Yuan

Publisher
Elsevier Science
Year
1996
Tongue
English
Weight
454 KB
Volume
51
Category
Article
ISSN
0009-2509

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✦ Synopsis

This paper develops a new on-line parameter estimation strategy, which takes advantage of BFGS formula to update the inverse Hessian matrix, and one-dimensional search to accelerate the tracking speed. The dynamic model for fixed-bed reactors is lumped to a proper form for identification by double collocation. The gradients of the quadratic objective function with respect to the estimated parameters are obtained in a more accm~ate way. The method needs low intensive computation, proved to be superior to the traditional method, i.e. the recursive least squares algorithm with forgetting factor, in terms of the speed of tracking, robustness in the presence of errors of the model parameters, and the ability to handle nonlinearity of the fixed-bed reactor.

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