摘要
根据分解炉温度控制的实际生产情况,确定了三次风、煤粉和生料流量配比、阀门开度与分解炉温度之间的关系,建立了分解炉温度控制的数学模型。由于神经网络可以实现对复杂非线性对象进行有效的控制,因此选定神经网络中应用最广泛的BP神经网络作为控制算法,对三次风和煤粉阀门开度进行预测,为计算机进行计算处理提供了依据。在此基础上,设计了以工控机为核心的分解炉温度控制系统。实际运行结果表明,该控制系统稳定可靠,控制效果良好,满足了生产工艺的要求。
According to practical condition of temperature control of decomposing furnace, the relationship of specific flux, valve opening and temperature of decomposing furnace is determined and a mathematical model of temperature of decomposing furnace is proposed. Because neural network can control nonlinear object effectually, a control algorithm of BP neural network is chosen. And a control system of temperature of decomposing furnace is designed, of which the computer is core. The practical results show that the system is reliable and steady. Its control meets the requirements of process.
出处
《控制工程》
CSCD
2004年第1期63-65,共3页
Control Engineering of China
