Journal of System Simulation
Abstract
Abstract: According to the present situation of SCR flue gas dentration control system in thermal power plant, an optimum proposal that control valve and concentration transmitter are added in the inlet of the SCR reactor is presented, and the corresponding control strategy is given. At the entrance of the SCR reactor, the receding horizon algorithm combined with the single neuron adaptive algorithm and the artificial fish swarm algorithm (RSNAAFS) is used to control branch valves to pretreat NOX in the exhaust flue gas. At the outlet of the SCR reactor, the neural network based on feedback linearization algorithm (NNFL) is used to control the general valve to limit the concentration of NOX under the obligatory standard. The simulation result indicates that the presented strategy has a better effect on control quality compared with traditional control strategy, and has important practical significance.
Recommended Citation
Niu, Yuguang; Yan, Pan; and Huang, Wenyuan
(2019)
"Artificial Fish Swarm and Feedback Linearization of Flue Gas Denitration Control Based on Neural Network,"
Journal of System Simulation: Vol. 30:
Iss.
7, Article 34.
DOI: 10.16182/j.issn1004731x.joss.201807034
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss7/34
First Page
2707
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201807034
Last Page
2714
CLC
TP27
Recommended Citation
Niu Yuguang, Pan Yan, Huang Wenyuan. Artificial Fish Swarm and Feedback Linearization of Flue Gas Denitration Control Based on Neural Network[J]. Journal of System Simulation, 2018, 30(7): 2707-2714.
DOI
10.16182/j.issn1004731x.joss.201807034
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