摘要
以某焦化厂1#和2#焦炉集散控制系统的开发为背景,提出了前馈反馈控制方法来优化焦炉对象的燃烧控制.前馈模型根据物料燃烧和焦化过程的热平衡方程计算出前馈的偏差量,快速而直接地调整供气量;反馈采用BP神经网络自适应控制.针对焦炉生产过程的简化模型,在Matlab中实现了BP神经网络自适应控制算法.仿真研究表明该方法应用于焦炉控制是可行的.
Based on the distributed control systems of two coke ovens in some steel mill, a method with forward back and feedback control is presented to control the combustion of the coke ovens. In the forward back model, the equation of combustion and coke process are used to compute the bias. In the feedback model, the neural adaptive method is adopted to control the output temperature. The simulation results of the proposed algorithm applied to a simplified coke oven model show the feasibility of the method.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第8期909-912,916,共5页
Control and Decision
关键词
神经网络
自适应控制
前馈控制
反馈控制
Neural network Adaptive control Forwardback control Feedback control
