Design of a neural controller by inverse modelling

This paper deals with the development a neural controller (a control system using a neural network) and its application for the temperature control of an experimental semi-batch pilot-plant reactor equipped with a monofluid heating-cooling system. The neural controller design methodology is based on...

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Bibliographic Details
Published in:Computers & chemical engineering 1995-06, Vol.19, p.797-802
Main Authors: Dirion, J.L., Cabassud, M., Le Lann, M.V., Casamatta, G.
Format: Article
Language:English
Subjects:
batch reactor
inverse dynamics
neural controller
Neural network
process control
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Summary:This paper deals with the development a neural controller (a control system using a neural network) and its application for the temperature control of an experimental semi-batch pilot-plant reactor equipped with a monofluid heating-cooling system. The neural controller design methodology is based on the process inverse dynamics modelling : the learning data base is generated in an open-loop structure and the learning of the neural network is carried out by considering the future process outputs as the reference set-point. The first results presented deal with an ideal simulated system modelled by a first order system. They demonstrate the importance to take the time-delay of the plant into account. The second part is concerned with the real time application of such a technique to the temperature control of a semi-batch pilot- plant reactor and shows the real capability of the neutral networks in process control.
ISSN:0098-1354
1873-4375
DOI:10.1016/0098-1354(95)87132-2