摘要
针对焦炉集气管压力这类多变量非线性系统 ,提出了一种基于 PID神经网络和 RBF模糊神经网络的多变量解耦控制方案 ,RBF模糊神经网络对多变量对象进行解耦 ,PID神经网络控制器控制过程的动态特性 .工程应用表明 。
For the multi variable nonlinear system such as the collection pressure of coke ovens, this paper proposes an multi variable decoupling control algorithm based on a PID neural network and RBF fuzzy neural network, the RBF fuzzy neural network responds for the decoupling of the plant and PID neural network responds the dynamical property of plant output. The real world application shows that the proposed control strategy successfully solved the process control problem of the complex plant such as the collection pressure of coke ovens.
出处
《小型微型计算机系统》
CSCD
北大核心
2002年第5期561-564,共4页
Journal of Chinese Computer Systems
基金
湖南省中青年科技基金项目 (99JZY2 0 79)
关键词
模糊神经网络
多变量解耦控制
动态耦合特性
自学习算法
智能梯度法
multi variable nonlinear control
dynamical couple characteristic
fuzzy neural networks
self learning algorithm
intelligent gradient approach
