基于Volterra基函数网络的自适应逆控制方法  

Adaptive Inverse Control Based on Volterra Polynomial Basis Function Neural Networks

作　　者：党映农[1] 韩崇昭[1] 

机构地区：[1]西安交通大学,西安710049

出　　处：《西安交通大学学报》2000年第9期8-12,共5页Journal of Xi'an Jiaotong University

基　　金：国家自然科学基金资助项目! (696740 0 9)

摘　　要：提出了一种基于Volterra基函数 (VPBF)网络的非线性系统自适应逆控制方法 .对象和逆控制器各用一个VPBF网络表示 ,应用正交最小二乘算法进行离线网络结构确定和权值初始化 ,构造了一种动态归一化非线性最小均方 (DNNLMS)权值更新算法 ,以进行网络权值的在线学习 .仿真结果表明 ,该方法具有算法简单、学习速度快、鲁棒性能好等优点 .An adaptive inverse control method for nonlinear systems is proposed by using the Volterra polynomial basis function (VPBF) neural networks. VPBF neural networks were used to describe both the plant and the inverse controller. The structure and initial parameters of the VPBF neural networks were determined by using the orthogonal least squares algorithm. A dynamical normalized nonlinear least mean square (DNNLMS) algorithm was developed for on line weights learning. The proposed method is simple and has fast learning rate.

关 键 词：非线性系统 自适应逆控制 Volterra基函数网络 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]