基于改进自适应GPC的锅炉主蒸汽温度预测控制  

Predictive Control for the Boiler Main Steam Temperature based on Improved Adaptive Generalized Predictive Control

作　　者：谢七月[1] 周超 XIE Qi-yue;ZHOU Chao(Hunan Province 2011Collaborative Innovation Center of Clean Energy and Smart Grid,School of Energy and Power Engineering,Changsha University of Science &Technology,Changsha,China,Post Code :410114)

机构地区：[1]长沙理工大学能源与动力工程学院清洁能源与智能电网湖南省2011协同创新中心,湖南长沙410114

出　　处：《热能动力工程》2018年第12期86-92,共7页Journal of Engineering for Thermal Energy and Power

基　　金：国家自然科学基金(61304019;61673401;51674042);湖南省教育厅重点项目(17A005)~~

摘　　要：为了维持锅炉主蒸汽温度良好的控制品质,提出基于改进自适应广义预测控制(A-PIGPC)的主蒸汽温度预测控制方法。首先,对锅炉主蒸汽温度高阶模型进行降阶,建立一阶加纯滞后(FOPDT)模型,并根据实际情况考虑了输入约束条件;然后,对广义预测控制(GPC)算法的优化性能指标进行改进,使其具有PI反馈结构,采用带遗忘因子的递推最小二乘法(RLS)在线辨识模型参数,满足变工况的需要;最后,进行MATLAB仿真验证所提方法的有效性。研究表明:A-PIGPC优于常规PID和GPC、预测函数控制(PFC)控制方法,且在变工况下有较强的鲁棒性。In order to maintain good control quality of the boiler main steam temperature an A-PIGPC (improved adaptive generalized predictive control)is proposed for the main steam temperature control system.First of all,FOPDT (first order plus dead time)model is established by reducing the higher order model of the main steam temperature of boiler,and considering the input constraints according to the actu- al situation.Then,the optimal performance index of GPC (generalized predictive control)algorithm is im- proved to have PI feedback structure,and RLS (recursive least squares)with forgetting factor is applied to identify the parameters of the model to meet the requirements of variable working conditions.Finally, the effectiveness of the proposed method is verified by Madab simulation.The simulation results show that A-PIGPC is superior to conventional PID,GPC,and PFC (predictive function control)control methods, and it also has strong robustness under variable conditions.

关 键 词：主蒸汽温度系统 改进GPC 带遗忘因子的递推最小二乘法 PI反馈 MATLAB仿真 

分 类 号：TK32[动力工程及工程热物理—热能工程]