This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.

提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。

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An adaptive neuron control method is presented. By use of this kind of controller, an intelligent control system is designed, and its learning rules are also presented.

该文给出了一种自适应神经元的控制方法，设计了神经元网络作为控制器的智能控制系统，给出了学习规则。

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System identification plays an important role in high performance automation technologies such as adaptive control and learning control.

系统辨识是高性能自动化技术(如适应控制与学习控制)中的重要内容。

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