烧结配料系统的单神经自适应内模控制  

Single Neuron Adaptive Internal Model Control for Sintering Blending System

作　　者：王随平[1] 彭亮[1] 戴畅[1] 

机构地区：[1]中南大学信息科学与工程学院

出　　处：《可编程控制器与工厂自动化（PLC FA）》2011年第10期107-109,共3页Programmable controller & Factory Automation(PLC & FA)

摘　　要：烧结配料过程中的物流流量因受到许多不确定因素的影响而波动很大,具有大惯性、大时滞、非线性的特点,它的控制很难通过传统的控制理论与方法来解决,为了提高配料的的精确度和稳定性,本文提出了单神经自适应内模控制器。通过仿真实验表明,该控制方法是有效的,它不仅具有良好的动、静态性能,还有很强的鲁棒性和自学习能力。The material flow in the sintering blending process was impacted by many uncertainfactors and fluctuates greatly with characters of high nonlinear and large lag￡It is hard to solvethe sintering blending control problem by conventional control theory and methods￡ln order toimprove the accuracy and stability of the sintering blending￡-a single neuron self-adaptiveinternal model controller was proposed.By the simulation experiment,the control strategy iseffective￡-and this control method can achieve not only good dynamic and static performance￡-but also strong robustness and self-study capability simultaneously

关 键 词：烧结配料 单神经元 自适应 内模控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]