基于径向基神经网络辨识的电弧炉电极调节系统内模控制  

IMC of the Electric Arc Furnace Electrode Regulator System Based on RBF Neural Network Identification

作　　者：程少帅 马开明 

机构地区：[1]沈阳众义达科技有限公司,沈阳110004 [2]中核核电运行管理有限公司,嘉兴314300

出　　处：《电气工程学报》2015年第10期59-63,共5页Journal of Electrical Engineering

摘　　要：处理非线性和电弧炉电极调节系统的时变特性,内模控制器的设计。该控制器由两个RBF神经网络,用来确定控制对象和它的逆,以消除稳态误差,让输出跟踪输入。中心向量和网络的形状参数进行在线调节,从而加快了收敛速度,提高了抗干扰能力。仿真结果验证了该方法的有效性。To deal with the nonlinear and time-variant characteristic of the electrode regulator system in arc furnace,an IMC controller is designed.The controller composes by two RBF neural networks,which are used to identify the controlled object and its inverse,from this to eliminate steady-state error and let output track input.Center vectors and the shape parameters of the networks are adjusted online,which speeds up the convergence rate and improves anti-jamming capability.Simulation results verify the effectiveness of the method.

关 键 词：内模控制 RBF神经网络 在线调整 非线性时变 

分 类 号：TM76[电气工程—电力系统及自动化]