摘要
针对环氧乙烷反应器控制存在的问题,采用一种改进的控制方法。首先基于径向基神经网络系统建立环氧乙烷反应器模型,并由模型输出值调整反应器氧气进料控制的期望值,然后通过提高氧气进料控制的快速性和准确性来实现对环氧乙烷反应器的优化控制。仿真结果验证了改进控制方案的有效性。
Modified control scheme was adopted for the controlling problems existing in the ethylene oxide reactor.Firstly,the model of ethylene oxide reactor was built based on RBF neural network,and the expected set value of the controller for the feed of oxygen was adjusted by the output value of the model.Then optimal control for the ethylene oxide reactor was realized by enhancing the efficiency and rate of the control for the feed of the oxygen.Simulation result demonstrates the validity of the proposed control scheme.
出处
《化工自动化及仪表》
CAS
北大核心
2010年第6期29-31,共3页
Control and Instruments in Chemical Industry
关键词
环氧乙烷反应器
神经网络
优化控制
ethylene oxide reactor
neural network
optimal control
