北京航空航天大学学报 ›› 2004, Vol. 30 ›› Issue (09): 889-892.

• 论文 • 上一篇    下一篇

一种基于混沌神经网络的拟人智能控制方法

石晓荣, 张明廉   

  1. 北京航空航天大学 自动化科学与电气工程学院, 北京 100083
  • 收稿日期:2003-06-06 出版日期:2004-09-30 发布日期:2010-09-21
  • 作者简介:石晓荣 (1977-),女,陕西西安人,博士生,sxr@dept3.buaa.edu.cn.
  • 基金资助:

    国家自然科学基金资助项目(60074021)

Human-imitating control based on chaotic neural networks

Shi Xiaorong, Zhang Minglian   

  1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2003-06-06 Online:2004-09-30 Published:2010-09-21

摘要: 提出一种基于混沌神经网络(CNN)的拟人智能控制方法.首先利用拟人智能控制理论得到定性控制律(线性或非线性),然后利用CNN实现控制律的定量化.Hopfield神经网络具有快速的优化能力,但容易陷入局部极小,将遍历性的渐变混沌噪声引入其中,形成具有快速全局优化能力的CNN.对二级倒立摆控制的仿真和实验结果均表明该方法有效.

Abstract: A control method was proposed, which combines the human-imitating control theory and the optimization capability of chaotic neural networks (CNN). Firstly, a qualitative control law(linear or nonlinear control law)was formed according to human-imitating control. Then, the qualitative control law was quantified by CNN. Hopfield neural network is recognized as a useful tool for optimization problems. However, it is often trapped to a local minimum solution. Therefore, gradually reducing chaotic noise is added to the networks to form a powerful globe optimization algorithm. Applying the proposed control method to a double inverted pendulum, the results of numerical simulations and experiments both demonstrate the valid of this control method.

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