Open AccessState variable-fuzzy prediction control strategy for superheated steam temperature of thermal power units
Author(s) -
Xuan Tu,
Jinsen Shi,
Kun Yao,
Jie Wan,
Fei Qiao
Publication year - 2021
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci2106083t
Subject(s) - control theory (sociology) , computer science , fuzzy logic , thermal power station , controller (irrigation) , state observer , temperature control , model predictive control , state variable , grid connection , control engineering , grid , control (management) , engineering , mathematics , nonlinear system , artificial intelligence , agronomy , physics , thermodynamics , geometry , quantum mechanics , biology , waste management
With the large-scale grid connection of new energy power, the random fluctuation existing in the power system is intensified, which leads to frequent fluctuation of load instructions of thermal power units. It is of great significance to improve the variable load performance of the coal-fired units. It is more difficult to control the superheated steam temperature (SST). In order to improve the control performance of SST, a state variable fuzzy predictive control method is proposed in this paper. Firstly, Takagi-Sugeno fuzzy state observer is used to approximate the non-linear plant of the SST. At the same time, based on the state observer, a fuzzy state feedback controller is designed to improve its dynamic characteristics. Thirdly, based on the extended predictive model of the state feedback controller, a model predictive controller is designed to realize the SST tracking control. Dynamic simulation shows the effectiveness of the strategy.