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Title:
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Neuro-fuzzy control in a steam boiler
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Author(s):
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Published by:
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Publication date:
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ECN
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1998
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ECN report number:
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Document type:
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ECN-RX--98-030
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Article (scientific)
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Number of pages:
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7
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Published in: Paper, presented at the 6th European congress on intelligent techniques and soft computing (EUFIT'98), Aachen, Germany, Septembe (), , , Vol., p.-.
Abstract:
A neuro-fuzzy controller has been designed for a burner system in anindustrial gas-fuelled steam boiler that maximises energy efficiency under
the constraint of a maximum NOx emission level. It can act as a feedforward
precompensator, generating nearly optimal control actions even under strong
load changes or large variations in fuel gas composition. The fuzzy network
of the controller was trained on real historical process data. The underlying
assumption is that the non-linear static map generated by the neural network
can adequately represent the system's inverse dynamic behaviour in the ranges
of interest. In this controller design strategy, process modelling is not
necessary. The controllability was hence improved, resulting in a higher
boiler energy efficiency and lower electrical energy consumption by the
recycle flow ventilator, while the NOx emission limit is not exceeded. 4 refs.
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