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�������պ����ѧѧ�� 2004, Vol. 30 Issue (09) :889-892    DOI:
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Human-imitating control based on chaotic neural networks
Shi Xiaorong, Zhang Minglian*
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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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.
Keywords�� neural networks   automatic control systems   optimization algorithms   chaos     
Received 2003-06-06;
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About author: ʯ���� (1977-),Ů,����������,��ʿ��,sxr@dept3.buaa.edu.cn.
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ʯ����, ������.һ�ֻ��ڻ�����������������ܿ��Ʒ���[J]  �������պ����ѧѧ��, 2004,V30(09): 889-892
Shi Xiaorong, Zhang Minglian.Human-imitating control based on chaotic neural networks[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2004,V30(09): 889-892
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