A new kind of FCMAC (Fuzzy Cerebellar Model Articulation Controller) is presented.
提出了一种模糊小脑模型神经网络(FCMAC)。
An introduction is provided for the image-based visual servo system of three-dof planar robot combined with DSP image processing system and FCMAC control method.
以三自由度平面机器人为研究对象，采用DSP图像处理系统，并将FCMAC控制方法应用到基于图像的机器人视觉伺服系统中。
The proposed FCMAC is applied on robotic tracking control system to counteract the disadvantageous influences of nonlinearities and uncertainties in robotic system.
所提出的FCMAC被应用于机器人的轨迹跟踪控制系统以克服机器人系统中非线性和不确定性因素的影响。
A direct inverse control scheme of FCMAC neural network is presented for vector control AC servo system. The principle analysis and the design realizing process of the system are given in detail.
本文针对矢量控制交流伺服系统，提出了一种模糊小脑模型神经网络直接逆控制的方案，给出了较详细的原理分析及实现过程。
FCMAC based controller structure and a simple learning algorithm were also proposed. In the learning algorithm only small parts of parameters of the FCMAC were adjusted at each learning iteration.
给出一种基于FCMAC的自学习控制器的结构及合适的学习算法，这种网络每次学习少量参数，算法简单。
FCMAC based controller structure and a simple learning algorithm were also proposed. In the learning algorithm only small parts of parameters of the FCMAC were adjusted at each learning iteration.
给出一种基于FCMAC的自学习控制器的结构及合适的学习算法，这种网络每次学习少量参数，算法简单。
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