北京航空航天大学学报 ›› 2001, Vol. 27 ›› Issue (2): 153-156.

• 论文 • 上一篇    下一篇

基于神经网络自适应稳定PID控制方法的研究

扈宏杰, 尔联洁, 刘强, 陈敬泉   

  1. 北京航空航天大学 自动控制系
  • 收稿日期:1999-11-01 出版日期:2001-02-28 发布日期:2010-09-27
  • 作者简介:扈宏杰(1962-),男,辽宁新民人,博士生,100083,北京.
  • 基金资助:

    航空基础科学基金资助项目(00E51022)

Study of GPS/MM Integrated Navigation System for Vehicle Positioning Based on D-S Evidence Reasoning

HU Hong-jie, ER Lian-jie, LIU Qiang, CHEN Jing-quan   

  1. Beijing University of Aeronautics and Astronautics, Dept. of Automatic Control
  • Received:1999-11-01 Online:2001-02-28 Published:2010-09-27

摘要: 经典的基于对象精确数学模型的PID控制方法的自适应性较差,难以适应具有非线性、时变不确定性的被控对象.神经网络控制算法的稳定性又受到迭代初值的影响,且算法复杂.为此提出了一种基于RBF神经网络的、结构简单的、稳定的PID直接自适应控制方法.讨论了控制器参数迭代初值选取的基本原则,并给出了在保证系统稳定性前提下参数的迭代算法.仿真研究结果表明,该方法的鲁棒性和跟踪性能均优于经典PID方法.

Abstract: Classic PID control method which is based on precise mathematical model has poor adaptivity and is not adaptive to nonlinear and time-variant plants.Conventional neural network is always complicated and its stability often suffers from the effect of initial weight value selecting.A simple stable direct adaptive PID control algorithm is proposed, which is based on RBF neural network.To guarantee the system stability and improve the system precision, initial weight value selecting problem for the neural network is discussed and corresponding iterative algorithm is provided. Simulation results indicate that the system robustness and tracking performance are superior to those of classic PID method.

中图分类号: 


版权所有 © 《北京航空航天大学学报》编辑部
通讯地址:北京市海淀区学院路37号 北京航空航天大学学报编辑部 邮编:100191 E-mail:jbuaa@buaa.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发