Engineering Mechanics

Proceedings Vol. 10 (2004)

ENGINEERING MECHANICS 2004

Copyright © 2004 Institute of Thermomechanics, Academy of Sciences of the Czech Republic, Prague

 

Vítek T., Havlena V.
pages 313 - +8p., full text

In order to improve the accuracy of process data, the data reconciliation method can be used. Data reconciliation takes advantage of physical and chemical balances which can be arranged to decrease the measurement errors. Data processed by data reconciliation are in harmony with the physical model of technology which is further used for optimization of the process. This article claims to formulate the data reconciliation task in case of the heat system - the steam generator. The final form of problem is to minimize quadratic function subject to bilinear constrains. From various possible solutions we chose the gradient projection method and the sequential quadratic programming method (SQP). These too methods are compared in terms of efficiency and robustness in solving the reconciliation of steam generator’s data.

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