基于神经网络的真空烧结炉温度控制系统的研究  

Research on the Temperature Control of Vacuum Sintering Furnace Based on Neural Network

作　　者：谭梅[1] 程春红[1] 吕聪[1] 

机构地区：[1]湖南工程学院电气系,湖南湘潭411101

出　　处：《测控技术》2006年第2期31-32,53,共3页Measurement & Control Technology

摘　　要：以真空烧结炉温度控制系统为研究对象,提出了一种基于 BP 神经网络整定的 PID 控制方法,并给出了系统设计及软件开发。由于神经网格所具有的任意非线性表达能力,可以通过对系统性能的学习来实现具有最佳组合的 PID 控制。实验结果表明,用该方法整定的 PID 控制系统,逼近精度高,鲁棒性好。Taking the temperature controlling system of vacuum sintering furnace as the object of study, the PID controlling method based on BP neural network is put forward, and the system design and software development is also presented. Possessing the arbitrary nonlinear expressiveness, the neural network can help to realize the PID control with the best combinations by means of the understanding of the system performance. The network has high precision and good robustness. Results of the experiment are satisfactory and prove the method to be feasible and effective.

关 键 词：真空烧结炉 温度控制 BP神经网络 PID控制 

分 类 号：TP275[自动化与计算机技术—检测技术与自动化装置]