摘要
针对直流锅炉主蒸汽温度控制系统复杂,控制链跨度大的问题,在分析了主汽温控制系统特点的基础上,提出一种基于逆向传递策略的串级系统网络化预测控制方法,并采用遗忘因子递推最小二乘法(RLS)对子系统进行在线辨识,适应直流锅炉变工况需要。为了使喷水减温具有较大的调整范围,通过主汽温导前区在线辨识结果实现对逆向传递策略中设定值的设计;并用预测控制的约束条件,保证中间点温度和各级过热器出口具有足够的过热度。将该方法应用于电厂过热汽温控制系统进行仿真研究,结果表明该方法能较好地适应对象特性的变化,且控制效果明显优于常规串级控制系统。
In once-through boiler, main steam temperature control system was complex, which had the large control chain span. According to the analysis of the characteristics of main steam temperature control system, a networked predictive control method based on reverse transfer strategy for the cascade system was presented. The recursive least squares（RLS）with forgetting factor was used to identify subsystems, which was adapted to the need of once-through boiler＇s variable conditions. In order to make the desuperheat spray have the enough adjustment range, the setting points of the reverse transfer strategy were designed by the online identification of the main steam temperatures-＇ leading segments. Constraint conditions of predictive control were used to ensure that the intermediate point＇s temperature and the superheater outlet temperatures had enough superheat. A simulation for superheat steam temperature control system of one once-through power plant was carried out by the presented method. The result shows that the control system＇s effect is better than the conventional cascade control system.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2015年第19期4981-4990,共10页
Proceedings of the CSEE
关键词
直流锅炉
主汽温度
网络化预测控制
带遗忘因子的递推最小二乘法
在线辨识
逆向传递策略
约束条件
once-through boiler
main steam temperature
networked predictive control
least square method with forgetting factor
online identification
reverse transfer strategy
constraint conditions
