BP神经网络在流量比值控制系统中的应用  

Application of BP Neural Network for Flow-ratio Control System

作　　者：丁芳[1] 贾翔宇[1] 倪杰 

机构地区：[1]中国民航大学航空自动化学院,天津300300 [2]上海航空股份有限公司,上海200042

出　　处：《机床与液压》2007年第7期193-195,197,共4页Machine Tool & Hydraulics

摘　　要：针对在PCT-2型过程控制装置进行流量比值控制时,PID参数难以整定的问题,提出了一种基于神经网络自适应的PID流量比值控制方法。该算法利用BP神经网络的非线性表示能力,通过系统的自学习来实现具有最佳组合的PID控制。这种方案达到了在线实时控制的目的。实验表明:在流量比值控制系统中,基于BP神经网络的PID控制算法比普通PID控制算法具有更好的动态性能和鲁棒性,能取得很好的控制效果。Aimed at the problem that it is difficult to confirm the PID-parameters when controling flow-ratio on the process control system experimental equipment （PCT-2）, a method for flow-ratio control was put forward based on neural network self-adaptive PID algorithm. The algorithm uses a nonlinear BP neural network to achieve the best combination of PID control through the self-study of the system. This strategy achieves the goal of online real-time control. The experiment proves that the PID control algorithm based on BP neural network algorithm is better than the ordinary PID algorithm on the dynamic performance and robustness, and can achieve good control.

关 键 词：BP神经网络 PID算法 流量比值 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]