基于网络的开放式结构和嵌入式结构的通用运动控制器逐步成为自动化控制领域里的主导产品之一。
General movement controller, which is based on the open and embedded structure of Internet, is gradually becoming one of the main products in automatic control field.
采用模糊神经网络结合常规PD控制器的方法来进行机器人的运动控制，提出了提取模糊规则的方法。
Fuzzy Neural Network combined with conventional PD controller is used for the kinematics control and a fuzzy rule extraction method is put forward.
探讨了用于运动控制的单神经元pid控制器的结构与基于BP网络的模糊自适应PID控制。
The structure of single neuron PID controller for motion control and the fuzzy adaptive PID control based on BP networks are researched on.
本文提出一种基于T -S模型的变结构模糊神经网络直接逆模型控制器，并将其应用于移动机器人的运动控制中。
A direct inverse model controller of fuzzy neural network with changeable structure based on t s inference is presented in this paper and it is used to the motion control of mobile robot.
然而，目前常用的运动控制器的体系结构存在很多缺陷，如体积过大，不支持网络通信。
However, the architecture of current motion controller has many shortcomings, such as huge size, not supporting network communication.
作者运用该神经网络算法设计了水下机器人的运动控制器。
The algorithm was applied to the control of an autonomous underwater vehicle designed by HEU.
讨论了一种基于双映射神经网络的机械臂运动控制器。
The application of a robotic manipulator based on mutual mapping neural network(MMNN) is discussed.
针对六自由度并联平台运动控制精度不高的缺点，结合人工神经网络的优点，提出了一种动态模糊神经网络(DFNN)控制器来控制并联平台。
Aiming at the low control accuracy of 6-dof parallel platform, a dynamical fuzzy neural network (DFNN) was proposed to control the parallel platform which had advantages of artificial neural networks.
以六自由度运动平台为研究对象，分析了平台的运动学和动力学问题，采用了CMAC神经网络作为控制器，实现运动轨迹的跟踪。
This paper analyzed the kinematics and dynamics of the 6 DOF platform, and adopted CMAC Neural Networks as controller to realize tailing track.
以六自由度运动平台为研究对象，分析了平台的运动学和动力学问题，采用了CMAC神经网络作为控制器，实现运动轨迹的跟踪。
This paper analyzed the kinematics and dynamics of the 6 DOF platform, and adopted CMAC Neural Networks as controller to realize tailing track.
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