Multi-model Predictive Function Control Based on Neural Network and Its Application to the Coordinated Control System of Power Plants
The coordinated control system of boiler-turbine unit in power plants is a complicated multivariable system with nonlinear, uncertainty and strong coupling. In this paper the algorithm of multi-model predictive function based on neural network is proposed and it is applied in a 500MW unit. Firstly, several linearized models of the unit on different working conditions are obtained with small deviation linearized method and the global predictive model is gained by the method of neural network weights. Then, the control variables are calculated by predictive function controller. Finally, the simulation results testify the validity of this control algorithm.
neural network multi-model predictive function linearized models
Guolian HOU Haitao LIU Yi SUN Jianhua ZHANG
Department of Automation, North China Electric Power University, Beijing, 102206
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
3950-3954
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）