摘要
如何将机组主蒸汽温度快速地控制在额定范围之内是火电厂热工过程控制面临的主要难题。针对超临界锅炉机组的主蒸汽温控制问题,提出一种基于神经模糊模型的火电机组主蒸汽温度自适应PID控制方案。根据采集到的减温水流量、高温过热器入口温度、主蒸汽流量、主蒸汽温度数据建立机组主蒸汽温度神经模糊模型,以此模型为基础实施主蒸汽温度自适应PID串级控制。内环采用PI控制器克服内部扰动,从而减少扰动对于导前汽温的影响,再将内环PI闭环控制系统及惰性区作为广义被控对象实行单神经元PID控制,通过主蒸汽温度额定值和实际输出值之间的误差对控制器参数进行在线调节,最终达到对过热器的控制。仿真实例验证了所提出的方法的有效性。
How to quickly control the main steam temperature to the setpoint is difficult problem in the field of fire power station con- trol. Considering the control problem of the main steam temperature of super critical boiler machine set, a neuro-fuzzy model based a- daptive PID cascade control for the main steam temperature of fire electrical engineering set is proposed in this paper. A neuro-fuzzy model for main steam temperature is established by using the information of attemperation water flow, inlet temperature of high tempera- ture superheater, main steam flow and the main steam temperature. Then the adaptive PID cascade control of main steam temperature is implemented. A PI controller is employed in the inner loop to overcome inner disturbance, which can decrease the influence of the lead- ing area＇s differential temperature. Then the single neuron PID controller （SNAC） is implemented to control the called generalized process, which includes PI closed loop and inert segment. This controller is adjusted to eliminate the error between the predicted value and the output value. Finally, the effectiveness of this methodology is verified by simulation example.
出处
《控制工程》
CSCD
北大核心
2013年第5期877-881,共5页
Control Engineering of China
基金
国家自然科学基金项目(61004019)
教育部博士点基金(20093108120013)
上海市科委国际合作项目(12510709400)
上海大学"十一五"211建设项目资助
