热风炉燃烧过程智能优化控制方法的研究

Intelligent Optimal Control Method Study of Burning Process in Hot Blast Stove

摘要:

为了实现在不同工况条件下通过调整空燃比使热风炉燃烧系统保持在能耗最低、效率最高下运行,根据高炉生产的特点和蓄热式热风炉燃烧方式,设计了以模糊BP神经网络为智能优化算法的自寻优控制策略,实现了PID控制器参数实时、动态、精确的调整,实现了动态PID参数的准确调整,保证了煤气流量和空气流量的合理比值；经仿真结果表明,该系统不但有效地解决了传统热风炉的燃烧控制系统非线性、建模难和强耦合性的问题,而且使热风炉处于安全、节能的燃烧状态。

Abstract:

In order to make the combustion system of the hot blast stove run at the lowest energy consumption and with the best efficiency through adjusting the air-fuel ratio under different working conditions, the self-optimizing control strategy including the intelligent optimization algorithm of the fuzzy BP neural network was designed. Real-time, dynamic and accurate adjustments of PID controller parameters were achieved and the rational ratio of gas flow rate and airflow rate was guaranteed. Simulation results showed that, this system effectively solved nonlinear, modeling and strong coupling problems of the combustion control system in the traditional hot blast stove and made the stove be in safe and energy-saving combustion condition.