航空学报 > 1997, Vol. 18 Issue (2): 163-167

非线性MIMO系统神经网络自适应方法及其在飞控中的应用

周煊, 史忠科   

  1. 西北工业大学自动控制系, 西安, 710072
  • 收稿日期:1996-02-13 修回日期:1996-07-30 出版日期:1997-04-25 发布日期:1997-04-25

NEURAL NETWORK BASED ADAPTIVE METHOD FOR MIMO NONLINEAR SYSTEM AND ITS APPLICATION TO FLIGHT CONTROL

Zhou Xuan, Shi Zhongke   

  1. Department of Automatic Control,Northwestern Polytechnical University, Xian, 710072
  • Received:1996-02-13 Revised:1996-07-30 Online:1997-04-25 Published:1997-04-25

摘要:

提出了一种非线性系统的对角自回归神经网络模型。为了实现MIMO系统自适应控制,采用自回归辨识网络对未知非线性系统进行辨识,并将被控对象的误差灵敏度信息用于对角自回归控制网络训练。辨识网络和控制网络都用动态BP算法训练。实际某型飞机纵向模型的仿真结果表明,运用这种控制结构可得到较好的控制效果。

关键词: 神经网络, 自适应控制系统, 动态BP算法

Abstract:

A method is presented for controlling unknown nonlinear MIMO systems by using diagonal recurrent neural network (DRNN). In this controlling scheme, unknown nonlinear plant is identified by a diagonal recurrent neuroidentifier (DRNI), and the sensitivity information of the plant is provided to a diagonal recurrent neurocontroller(NRNC). A dynamic backpropagation algorithm(DBP) is used to train DRNC and DRNI. The proposed approach is applied to a flight control system and the simulation results are included.

Key words: neural network, adaptive control system, dynamic backpropagation algorithm

中图分类号: