热风炉燃烧过程智能优化控制方法的研究

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。

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

In order to achieve the aims of keeping the lowest energy consumption and the highest efficiency in the combustion system by adjusting the air-fuel ratio under varying operation conditions. according to the characteristics of combustion system of the regenerative hot stove, an self-optimizing control policy was designed by the intelligent optimization algorithms, namely Fuzzy-BP network, and to realize that parameters of PID controller can be adjusted with real-time, dynamic, accurate,and to ensure the reasonable ratio of gas flow and air flow.Simulation results show that the system not only can effectively solve the traditional problem of the combustion control system of hot blast stove such as non-linear, modeling and coupling, but also the hot blast stove is combustion state in the safe, energy-saving.