单神经元PID算法在流量比值控制中的应用

针对在PCT-2型过程控制装置进行流量比值控制时．PID（proportional integral differential controller）参数难以整定的问题，提出一种基于单神经元自适应的PID流量比值控制方法，使PID参数实现自整定。该算法利用单神经元的自学习和自适应能力、结构简单和易于计算的特点与PID算法相结合，形成了一种新型的智能PID流量比值控制方法．其可以解决传统PID调节器不易在线实时进行参数整定、难于对一些复杂过程和慢时变系统进行有效控制的不足。实验结果表明：这种控制方法不仅容易掌握、精度高，且具有一定的实用价值。

Application of Single Neuron Algorithm for Flow-Ratio Control System

Aiming at the problem that it is difficult to confirm the PID-parameters when we do the experiment of Flow-ratio on the process control system experimental equipment of PCT-2,this paper advances a method of PID algorithm for Flow-ratio control,which is based on the single neuron algorithm and makes the PID parameters achieve self-tuning. Single neuron algorithm has the ability of self-study and self-confirm,and It is simple and easy to compute. This paper combines the two algorithms to be a new PID control method for Flow-ratio,which can offset some shorts that PID regulator is difficult to adjust parameter on line real-timely and cannot supply effective control for some complicated process and Slow Time-variable system. Lab experimentations show that the method of intelligent control is not only simple and exactitude but also has a great practical value.