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中文摘要：
该文研究了不确定非线性蔡氏电路混沌系统的动态神经网络在线辨识和跟踪控制问题。利用无源技术得出梯度下降算法调整神经网络辨识器权值的稳定性定理，然后在辨识模型基础上设计局部优化控制器，将蔡氏混沌系统镇定到期望目标轨迹，并保证跟踪误差有界。数值仿真结果表明了所提出方法的有效性。
英文摘要：
On-line identification and following control of nonlinear uncertain Chua＇s chaotic system using dynamic neural networks are studied in this paper. The passive technique is applied to access properties of neuro-identifier that the gradient descent algorithm for weight adjustment is stable. Then an optimal controller based on the identification model is designed to direct the Chua＇s chaotic system towards desired target trajectory, and the tracking error is guaranteed to be bounded. Finally, the simulations are provided to demonstrate the effectiveness of the approach proposed.
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