Neural Network Predictive Control of a Chemical Reactor
A. Vasičkaninová, M. Bakošová
Slovak University of Technology in Bratislava
Abstract
Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulated variable adjustments in order to optimize the future behaviour of a plant. MPC technology can now be found in a wide variety of application areas. The neural network predictive controller that is discussed in this paper uses a neural network model of a nonlinear plant to predict future plant performance. The controller calculates the control input that will optimize plant performance over a specified future time horizon. In the paper the neural network based predictive control for the continuous stirred tank reactor is presented.
Full paper
Session
Model Predictive Control (Poster)
Reference
Vasičkaninová, A., Bakošová, M.: Neural Network Predictive Control of a Chemical Reactor. Editors: Fikar, M., Kvasnica, M., In Proceedings of the 17th International Conference on Process Control ’09, Štrbské Pleso, Slovakia, 426–431, 2009
BibTeX
| @inProceedings{pc09-097, | ||
| author | = { | Vasičkaninová, A. and Bakošová, M.}, |
| title | = { | Neural Network Predictive Control of a Chemical Reactor}, |
| booktitle | = { | Proceedings of the 17th International Conference on Process Control '09}, |
| year | = { | 2009}, |
| pages | = { | 426-431}, |
| editor | = { | Fikar, M. and Kvasnica, M.}, |
| address | = { | Štrbské Pleso, Slovakia}, |
| publisher | = { | Slovak University of Technology in Bratislava}, |
| url | = { | http://www.kirp.chtf.stuba.sk/pc09/data/papers/097.pdf}} |