RBF-PID串级控制在加热炉温度系统中的应用研究

针对工业生产中加热炉物料出口温度的非线性、时变性、大滞后性等特点,无法建立精确的数学模型,并且为提高该系统控制的可靠性和安全性,达到精确控制。提出一种基于RBF(Radial Basis Function)神经网络的PID串级控制器,即先用建立的三层RBF神经网络在线辨识得到梯度信息,再用梯度信息在线整定PID控制的三个参数,最后将整定的PID控制物料出口温度-炉膛温度串级系统的主回路。仿真结果表明,RBF-PID串级控制较传统P I D串级控制有较强的鲁棒性,提高了控制品质,获得了更好的控制效果。

Study on furnace temperature system PID cascade control based on RBF neural network

Because of the nonlinear,time-varying and large delay characteristics of furnace temperature in industrial production,which can not establish a precise mathematical model.To improve the reliability and security of the system control and achieve precise control(PID Cascade control based on RBF) Radial Basis Function,neural network is proposed in this paper.Three neural network layers are created.Which can obtain gradient information through the RBF neural network on line identification in the control process...