State variable-fuzzy prediction control strategy for superheated steam temperature of thermal power units

Abstract

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.