基于RBF神经网络逆系统的多变量解耦控制  

Multivariable Decoupling Control Based on RBF Neutral Network Inverse System

作　　者：王丽萍[1] 董江辉 

机构地区：[1]上海建桥学院,上海201319 [2]天合汽车部件技术服务(上海)有限公司,上海200233

出　　处：《交通信息与安全》2009年第2期59-62,共4页Journal of Transport Information and Safety

摘　　要：针对工业生产过程中的多变量耦合系统难以实现解耦的问题,建立了一种改进的规划算法的RBF神经网络逆系统,构造了多变量神经网络控制器,用来对多变量耦合系统进行解耦控制。对一组给定的二变量耦合系统进行了仿真,结果表明:基于改进的进化规划算法的RBF神经网络逆系统的解耦控制不仅超调量小、响应速度快、控制精度高,而且具有很强的鲁棒性和自适应能力。该解耦控制使得解耦后的多变量系统具备良好的动、静态特性,达到了理想的控制效果。Since it＇s very difficult to decouple for multivariable coupling system in the industrial process control field, an inverse system of RBF neutral network was set up based on an improved evolutionary programming algorithm. Then, the multivariable neutral network controller was constructed, which can be used to decouple control for the multivariable coupling system. A double variable coupling system was simulated in computer. The simulation results show that RBF neutral network inverse system based on an improved evolutionary programming algorithm works well with small overshoot, quick response, high control precision, good robustness and adaptive ability. This decoupled multivariable control system has better static and dynamic performance and attains the ideal control effect.

关 键 词：解耦控制 RBF神经网络 逆系统 

分 类 号：TP130.6[自动化与计算机技术—控制理论与控制工程]