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.

The α-interval valued fuzzy sets defined on α-interval valued set

“…The concept of interval valued fuzzy set was introduced by Zadeh [1][2][3][4]. The properties of interval valued fuzzy set and fuzzy set were studied by researchers [5][6][7][8][9][10][11][12]. The properties of interval valued fuzzy sets on different structures particularly, topological properties were examined by Mondal and Samantha [13].…”

On some fundamental properties of α-interval valued fuzzy subgroups

“…The definition of interval valued fuzzy subgroups was given by Biswas [13]. Many authors studied interval valued fuzzy subgroups and fuzzy sets [14][15][16][17][18]. In this paper, D(I) represents all closed sub-intervals of unit interval --------------…”