Neural net based model predictive control
- 1 December 1991
- journal article
- research article
- Published by Taylor & Francis in International Journal of Control
- Vol. 54 (6) , 1453-1468
- https://doi.org/10.1080/00207179108934221
Abstract
Neural networks hold great promise for application in the general area of process control. This paper focuses on using a back propagation network in an optimization based model predictive control scheme. Since an analytical expression for the gradient of the neural net model can be derived and this expression can be calculated in parallel, extremely fast computation times are possible. The control approach is illustrated on a pH CSTR example.Keywords
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