期刊
IEEE TRANSACTIONS ON ENERGY CONVERSION
卷 21, 期 4, 页码 900-908出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEC.2005.853758
关键词
generalized predictive control; neuro-fuzzy networks; superheated 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. This is often difficult to achieve using conventional PI controllers, as power plants are nonlinear and contain many uncertainties. 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 that models the plant. The proposed. nonlinear controller is applied to control the superheated steam temperature of a 200-MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional cascade PI controller or the linear GPC is obtained.
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