Volume 30 Issue 09
Sep.  2004
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Shi Xiaorong, Zhang Minglian. Human-imitating control based on chaotic neural networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(09): 889-892. (in Chinese)
Citation: Shi Xiaorong, Zhang Minglian. Human-imitating control based on chaotic neural networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(09): 889-892. (in Chinese)

Human-imitating control based on chaotic neural networks

  • Received Date: 06 Jun 2003
  • Publish Date: 30 Sep 2004
  • 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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