核电站蒸汽发生器水位智能数据驱动控制  

Intelligent Data-driven Control for Steam Generator Water Level in Nuclear Power Plant

作　　者：赵文彬 王灵 陈凯 钱虹 费敏锐 ZHAO Wenbin;WANG Ling;CHEN Kai;QIAN Hong;FEI Minrui(Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronics Engineering and Automation,Shanghai University,Shanghai 200444,China;Shanghai Automation Instrumentation Co.,Ltd.,Shanghai 200072,China;School of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China)

机构地区：[1]上海大学机电工程与自动化学院,上海市电站自动化技术重点实验室,上海200444 [2]上海自动化仪表有限公司,上海200072 [3]上海电力大学自动化工程学院,上海200090

出　　处：《流体测量与控制》2021年第4期6-12,共7页Fluid Measurement & Control

摘　　要：核电站蒸汽发生器是压水堆核电站的重要设备之一,具有被控对象精确建模困难、控制性能及安全性要求高等特点。以核电站蒸汽发生器水位控制系统为对象,研究了基于人类学习优化算法的智能反馈⁃前馈虚拟参考反馈整定控制方法,在不需要被控对象及扰动对象数学模型的情况下,能直接设计出性能理想的反馈⁃前馈控制系统,在存在可测扰动的情况下能够提供预测补偿动作以抑制干扰。仿真实验结果表明:相比于其他控制方法,智能反馈⁃前馈虚拟参考反馈整定(FFIVRFTH)方法设计出的控制器具有更好的控制性能和良好的工程应用前景。Steam generator is one of the most important equipments in PWR nuclear power plant,which is difficult to model the controlled object accurately and requires high control performance and safety.In this paper,a novel data-driven control method called the feedback-feedforward intelligent virtual reference feedback tuning based on the human learning optimization(FFIVRFTH)is studied for the steam generator water level control system of nuclear power plant.The feedback-feedforward control system with ideal performance can be designed directly without the mathematical model of controlled object and disturbed object,and in the presence of measurable disturbance,predictive compensation can be provided to suppress the disturbance.Simulation results show that compared with other control methods,the controller designed by FFIVRFTH method has better control performance and engineering application prospect.

关 键 词：人类学习优化算法 核电站蒸汽发生器 智能虚拟参考反馈整定 反馈⁃前馈控制 可测扰动 

分 类 号：TL48[核科学技术—核技术及应用]