Résultats exploitables
Powerful systems for identification and control of highly non-linear processes using neural networks
The results are summarized in the following list of software developments and technical know-how:
a set of new identification and control schemes based on former schemes;
algorithms for training the neural networks, including genetic algorithms and stochastic methods;
comparisons between classical and advanced neural controllers;
software implementation and test of neural controllers for specific industrial applications defined by the endorsers;
specifications for an industrial research project to be carried out by the endorsers.
The project has developed, generalized and extrapolated a wider set of non-linear identification and control schemes than initially expected, based on the identification of algorithms and control algorithms. The models developed are highly oriented towards industrial applications. All these identification and control models have been tested with data from the proposed theoretical testbed plants, with simulated data from the testbed plants (including a binary NEREFCO petroleum distillation column), real data of penicillin fermentation from ANTIBIOTICOS and data based on other biochemical models. The models have been generalized and extrapolated for an important number of industrial applications.
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