东北大学学报(自然科学版) ›› 2004, Vol. 25 ›› Issue (7): 633-636.DOI: -

• 论著 • 上一篇    下一篇

一种新的模糊自适应控制方法

张明君;张化光   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院 辽宁沈阳 110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2004-07-15 发布日期:2013-06-24
  • 通讯作者: Zhang, M.-J.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60274017);;国家教委博士点基金资助项目(20011045023);;沈阳市自然科学基金资助项目(1022033 1 07)·

Fuzzy adaptive control scheme

Zhang, Ming-Jun (1); Zhang, Hua-Guang (1)   

  1. (1) Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2004-07-15 Published:2013-06-24
  • Contact: Zhang, M.-J.
  • About author:-
  • Supported by:
    -

摘要: 针对未知的非线性不确定系统,提出了一种基于广义模糊双曲正切模型的模糊自适应控制方法·该方法采用广义模糊双曲正切模型作为未知的非线性对象的辨识器,以此为模糊自适应控制器提供参数自调整必需的梯度信息·通过与其他的辨识器比较,说明了广义模糊双曲正切模型辨识器具有辨识参数少,辨识复杂性较小,易于提高逼近精度的优点·自适应控制器的梯度算法使被控对象的输出能很好地跟踪期望输出·仿真结果表明,此控制方案对未知的非线性系统的输入有很强的自适应跟踪能力·

关键词: 自适应控制, 非线性系统, 广义模糊双曲正切模型, 梯度信息, 辨识器

Abstract: A fuzzy adaptive control scheme based on generalized fuzzy hyperbolic model (GFHM) for unknown nonlinear uncertain systems was proposed. Using GFHM as an identifier model for unknown nonlinear object, it can provide the gradient information necessary to the parameter self-adjusting of fuzzy adaptive controller. Comparing GFHM with other identifiers, the number of unknown parameters and identification complexity of GFHM are both less, while the accuracy of approximation is easy to be improved. Gradient algorithm of adaptive controller enables the output of controlled object to track the expected output very well. The simulation results show that the proposed scheme has powerful adaptive tracking ability for the signal input of unknown nonlinear system.

中图分类号: