本文提出了一种新型的神经网络结构的位置控制器，给出了该控制器的学习算法，并进行了数控机床位置伺服系统的仿真实验。
This paper proposes a new type position controller with neural network structure, gives it 's learning rule, and do the simulation experiment on position servo system of NC machine.
所设计的控制器能实现当地信号控制，并对系统运行点和网络结构的变化具有很强的鲁棒性。
The controllers designed can achieve the local control and possess good robustness when the working point and the structure of the system are changing.
埃勒森公共广播系统采用网络结构，而不是把各个系统要素连接到一个中央控制器上，而这样的结构使得系统设计获得了真正的自由。
The Elason PA system USES a network configuration rather than having all system elements connected to a central controller. This architecture gives real freedom in system design.
然后基于强化学习神经网络结构设计神经网络控制器以取得车速跟踪的自适应控制。
A neural network controller is designed based on reinforcement learning neural network framework to achieve adaptive control of velocity tracking.
在网络结构中建立的利用控制器网络协议的分布式微处理控制器减少了组装系统所必需的配线和连接。
Distributed microprocessor controllers established in a network configuration utilizing controller network protocols reduces the wiring and connections necessary for the assembled system.
在网络结构中建立的利用控制器网络协议的分布式微处理控制器减少了组装系统所必需的配线和连接。
Distributed microprocessor controllers established in a network configuration utilizing controller network protocols reduces the wiring and connections necessary for the assembled system.
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