Neuro-fuzzy Generalized Predictive Control of Boiler Steam Temperature
Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper, which consists of local GPCs designed using the local linear models of the neuro-fuzzy network. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant, in which much better performance than the traditional cascade PI controller or the linear GPC is obtained.
KeywordsSteam Temperature Generalize Predictive Controller Superheated Steam Temperature 200MW Power Plant Neurofuzzy Network
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