电弧炉电极 meaning in Chinese
arc furnace electrode
Examples
- Application to parameters of pid control based on genetic algorithm
电弧炉电极调节系统的自校正控制 - This paper introduces a simulation experimental system of 3 - phase ac arc furnace , developing a dsp based electric - arc furnace electric pole fluctuation control system
摘要介绍一种按照实际交流电弧的特性设计的三相交流电弧炉仿真试验系统，针对电弧炉电极升降控制提出了一种基于dsp的控制方案。 - Based on the theory of piecewise - linear , the paper carries through the research of model self - adaptive control to electric arc - furnace electrode regulator system ( eafers ) , and the digital self - adaptive control law of reference model is deduced . then , we designed the software simulation system of eafers according to the law , though which we studied the character of eafers . finally , a set of physical model of eafers , which is realized by hardware circuit , is designed according to the former research
本文首先应用分段线性化理论，对电弧炉电极调节系统的模型参考自适应控制算法进行了研究，推导出全数字化的模型参考自适应律；然后根据推导出的自适应律成功的设计出了的软件仿真系统，用软件对电弧炉电极控制进行了仿真研究；最后利用电子电路构造出一套完整的电炉炼钢电极控制硬件仿真系统，对电炉电极调节进行了实验室电路仿真研究。 - The paper presents a new e . a . f ( electric arc furnace ) adaptive control method based on a neural network ' s compensation by predicting . the neural network is used here to predict the condition of e . a . f , then to control an actual system by compensating the outputing of routine controller . the dynamic modification of the weighting value of a neural network by improved dbd algorithm serves as an adaptive method . hence the system can adapt itself better to the variations in load and external interference . which has yielded a satisfied control quality
电极调节器采用一种新的电弧炉电极自适应控制方法- - -基于神经网络预估补偿的自适应控制。采用神经网络预估对象状态，进而对常规控制器的输出做补偿以控制实际对象，利用改进的dbd算法动态修改神经网络权值作为自适应方法，使系统较好地适应负荷和外扰的变化，从而获得满意的控制质量。