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Details for article 3 of 7 found articles
| Title: |
CONTROL OF NITRIC OXIDE EMISSIONS FROM A LABORATORY COMBUSTOR USING ARTIFICIAL NEURAL NETWORKS |
| Author: |
Slanvetpan, T. Barat, R. B. |
| Appeared in: |
Combustion science and technology |
| Paging: | Volume 175 (2003) nr. 10 pages 1761-1782 |
| Year: |
2003-10 |
| Contents: |
An active control system based on statically trained, feed-forward, multilayer-perceptron neural networks was designed and demonstrated, by experiment and simulation, for NO and CO 2 from a two-stage laboratory combustor operated under staged-air conditions. The neural networks are arranged in two clusters for feed-forward/feedback control. The first cluster is a neural-network-based, model-predictive controller (NMPC) and is used to identify the process disturbance and adjust the manipulated variables. The second cluster is a neural-network-based Smith time-delay compensator (NSTC) and is used to reduce the impact of the long sampling/analysis lags in the process. NMPC and NSTC are efficiently simple in terms of the network structure and training algorithm. The controller based on NMPC/NSTC showed a superior performance over the conventional proportional integral derivative controller. The novel controller has also been demonstrated on a neural-network-based combustor process simulator. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 3 of 7 found articles
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