Possibility of neural networks controller for robot manipulators
Possibility of neural networks controller for robot manipulators
复制标题
机器人机械手神经网络控制器的可能性
DOI：
10.1109/robot.1990.126252
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发表时间：
1990
期刊：
影响因子：
--
通讯作者：
T. Yamada
中科院分区：
文献类型：
--
作者：
T. Yabuta;T. Yamada
通过与自适应控制理论的比较，阐明了神经网络控制器的特点。阐述了神经网络控制器体系结构和动态神经网络结构的分类。对神经网络控制器和自适应控制器的比较表明，线性两层神经网络控制器的结构与自适应控制器的结构相同，而非线性三层神经网络(PDP或并行分布式处理型)是自适应控制的非线性扩展。讨论了神经网络控制系统的稳定性，表明了广义Delta规则、被控对象和神经网络映射函数对系统稳定性的影响。最后，以力控制伺服机构为例，进行了神经网络控制器的实验。实验结果表明，神经网络的非线性Sigmoid函数可以补偿植物的非线性效应。
NN (neural network) controller characteristics are clarified by comparison with the adaptive control theory. The authors explain the classification of the NN controller architecture and the dynamic NN structure. A comparison between the NN controller and the adaptive controller shows that the framework of a linear two-layer NN controller is the same as that of the adaptive controller, and that the nonlinear three-layer NN (PDP, or parallel distributed processing type) is a nonlinear extension of the adaptive control. The stability characteristics of the NN control system, which shows the robustness effect of the generalized delta rule, the plant and the NN mapping function, are treated. Finally, NN controller experiments are demonstrated using a force control servomechanism. Experimental results suggest that the nonlinear sigmoid function of the NN can compensate for the nonlinear plant effect.<<ETX>>