基于自适应PSD预估算法的通风机风量控制  

Ventilator Air Volume Control Based on Adaptive PSD Estimation Algorithm

作　　者：王新[1] 翟景昌 

机构地区：[1]河南理工大学电气工程与自动化学院,河南焦作454000

出　　处：《计算机仿真》2014年第6期410-413,共4页Computer Simulation

基　　金：河南省高校科技创新人才支持计划项目(2008HASTIT022)

摘　　要：针对煤矿主要通风机风量控制系统的非线性、多干扰等特性,设计了一种单神经元自适应预估控制器,以实现通风机的变频调速控制。该控制器加入了无辨识控制中的增益自调整算法,以增强系统的自适应能力。利用单神经元的非线性逼近特性及自学习、自组织能力,弥补了Smith预估器解决模型不确定系统的不足。实验表明,在模型不匹配情况下,通风机风量控制系统采用改进的单神经元自适应预估算法进行控制,系统超调较小,稳定时间较短,具有较好的控制效果。In view of the nonlinear and the interference characteristics of the mine main ventilator air volume control system, a single - neuron adaptive forecast controller was designed to implement the variable frequency speed regulation of the ventilator. The controller gain was added the identification - free control algorithm to enhance the adaptive capacity of the system. The inadequacy of the Smith predictor in the uncertain model system wa made up by using the nonlinear approximation characteristics, the self - learning and the selforganizing capacity of the single - neuron. Simulation results show that the ventilator air volume control system has smaller overshoot, shorter setting time and better control effect by using the improved single - neuron adaptive forecast method when the model does not match.

关 键 词：单神经元 主通风机 史密斯预估 自适应 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]