Servicio de Información Comunitario sobre Investigación y Desarrollo - CORDIS


SINC-PRO Informe resumido

Project ID: G1RD-CT-2002-00756
Financiado con arreglo a: FP5-GROWTH
País: Netherlands

Development of on-line observers, model reduction techniques and self-learning process systems

On-line observers on the basis of extended Kalman filters and self-learning systems on the basis of neural networks have been developed. Model reduction for use in model predictive control of crystallization processes proved to be difficult due to the possibility of instable linear model and the highly non-linear character of the process. Model reduction of specified processes is possible, but a general solution of the model reduction was not developed. This problem has resulted in a new research program, coupling three companies with five universities to test different model reduction strategies in order to develop a general model reduction technique.

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Bosscheweg 143
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