MODELING AND CONTROLLER DESIGN OF SUPERHEATED STEAM TEMPERATURE SYSTEM BASED ON SVM COMBINING ADAPTIVE DMC

摘要：

Superheater steam temperature in power plant is the strong nonlinearity system.Sparse Least squares support vector networks (LSSVN) are proposed to model the superheated steam of power plant in this paper.The structure is obtained by equality constrained minimization.By combining the DMC with discount recursive partial least squares (DRPLS), a adaptive DMC control method based on discount recursive least square is presented.This method can reduce the effect of the old data, and tone up new data in order to improve the predictive capability of model.Model based on discounted-measurement has the better flexibility and adaptability.Simulation of a superheating system is taken in a 600MW supercritical concurrent boiler.The result shows that the proposed model can adapt to the strong nonlinear super-heater steam temperature process, and the control system performance is better than conventional PID cascade control.

关键词： Support vector networks ADMC DRPLS Superheater steam temperature

作者: JI-ZHEN LIU YONG WANG XIANG-JIE LIU

作者单位: Department of Automation, North China Electric Power University, Beijing, 102206, China Department of Automation, North China Electric Power University, Beijing, 102206, China;Department o

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 533-538

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）