基于动态递归神经网络的动态矩阵控制  

DYNAMIC MATRIX CONTROL BASED ON DYNAMIC RECURRENT NEURAL NETWORKS

作　　者：李峰[1] 李树荣[1] 

机构地区：[1]石油大学自动化系,山东东营257061

出　　处：《石油大学学报（自然科学版）》2001年第3期77-79,共3页Journal of the University of Petroleum,China(Edition of Natural Science)

基　　金：山东省自然科学基金资助项目 (项目编号 :Q96G0 2 15 0 )

摘　　要：给出了利用动态递归神经网络 (DRNN)重构一个非线性动态过程的方法 ,对权值调整算法进行了推导。采用的动态递归神经网络具有非线性系统状态观测器的结构特征 ,容易实现并进行稳定性分析。利用训练好的网络作为预估模型 ,设计了基于DRNN的动态矩阵控制算法。A nonlinear dynamic process is reconstructed by using dynamic recurrent neural networks (DRNN). The main idea is to construct an observer liked dynamic recurrent neural network to match a practical process. The network is trained by using input and output information of practical systems. An algorithm for adjusting weight matrix of the network is given. After a dynamic recurrent neural network is well trained, the so called DRNN based on predictive control can be implemented. The well trained dynamic recurrent neural network is taken as a predictive model in the proposed control scheme. A simulation for a nonisothermal continuous stirred tank reactor (CSTR) system demonstrates the effectiveness of the training algorithm and the control strategy.

关 键 词：非线性系统 动态递归神经网络 预估控制 重构 动态矩阵控制 

分 类 号：O231.2[理学—运筹学与控制论] TP13[理学—数学]