Application of Sine Cosine Egret Swarm Optimization Algorithm in Gas Turbine Cooling System

Abstract

Gas turbine cooling system is a typical multivariable, strongly coupled, nonlinear, and uncertain MIMO system. In order to solve the control problem of pressure, flow, and temperature of the system, an intelligent approach is necessary and more appropriate. The current system control mainly depends on the experience of the staff, which exists problems such as high labor intensity, low work efficiency and low control accuracy. Lack of accurate models make parameters tune difficultly, and ordinary control methods are difficult to control complex gas turbine cooling system. In this paper, the system transfer function model is built based on the field data obtained under different working conditions and system identification method. The diagonal matrix decoupling method is used to weaken the correlation between variables and achieve independent control among variables. When optimizing the parameters of the controller, Sine Cosine Egret Swarm Optimization Algorithm is proposed. Egret Swarm Optimization Algorithm is composed of Sit-And-Wait strategy, random walk, and encirclement strategy. The sit-and-wait strategy is prone to premature convergence, which makes the optimized parameters unsuitable for gas turbine cooling system. Sine Cosine Algorithm is introduced to randomly use the sine-cosine function for the pseudo-gradient of the weights of the observation equation, thus expanding the search range of the population. Friedman tests prove that the deviation of SE-ESOA is within the allowable range. The results show that the result of Sine Cosine Egret Swarm Optimization Algorithm is more stable and accurate, and it is more suitable for gas turbine cooling system, which solve the pressure, flow, and temperature control problems of complex systems.