对角递归神经网络在非线性内模控制中的应用  

Investigation on Nonlinear Internal Model Control Based on Diagonal Recurrent Neural Network

作　　者：吴志敏[1] 

机构地区：[1]江苏工业学院计算机科学与工程系,江苏常州213016

出　　处：《江苏工业学院学报》2006年第1期45-48,共4页Journal of Jiangsu Polytechnic University

摘　　要：提出一种基于对角递归神经网络的非线性内模控制方案,其内部模型和内模控制器的建立均由对角递归神经网络来实现,同时改进神经网络控制器的训练函数。仿真结果表明,改进的内模控制系统与基本BP神经网络内模控制系统相比,具有跟踪速度快,超调量小,以及对对象参数摄动具有较好的适应性。Nonlinear internal model control scheme based on diagonal recurrent neural network is presented. internal model and internal model controller are established by diagonal recurrent neural network. Meanwhile, this paper improves the training function of the neural network controller. The simulation resuits show that improved internal control has the faster tracking performance, less overshoot and better adaptability than the internal control based on BP neural network.

关 键 词：对角递归神经网络 内模控制 非线性系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]