【摘要】 热风炉系统通过焦炉煤气和高炉煤气分别控制热风炉拱顶温度和废气温度,二者在一个系统内燃烧,彼此相互交叉、相互影响。应用神经网络解耦控制技术,对燃料流量控制进行解耦,解耦后的子系统变为单变量系统,以实现燃料流量的最优控制和拱顶温度及废气温度的平稳控制。采用前馈补偿器完成解耦控制,解耦补偿器采用BP神经网络结构。根据现场实际数据仿真验证,表明该控制策略具有较好的动态跟踪特性,能满足复杂多变量控制系统的控制要求。更多还原

【Abstract】 Based on neural network decoupling control technique,fuel flow control of hot blast stove was decoupled and decoupled subsystem was transformed into a single variable system.Therefore,optimization control of fuel flow,and stable control of arch temperature and waste gas temperature were realized.Decoupling control was achieved by use of feedforward compensator with BP neural network structure.Simulation results show that the control strategy has better dynamic tracking property and can meet the requirement for complex multivariable control system.更多还原