基于神经网络控制器的机器人系统

L. Acosta, G.N. Marichal, L. Moreno, J.J. Rodrigo, A. Hamilton, J.A. Mendez
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引用次数: 22

摘要

本文提出了一种基于神经网络的控制算法。该控制算法已应用于具有高度非线性结构的机械臂。基于模型的机器人控制方法(如计算扭矩技术)需要大量的计算时间,如果所选择的特定模型结构不能正确反映所有动力学,则可能导致控制性能差。本文提出的控制方法取得了满意的效果。这里假设了一个分散的模型,其中控制器与每个关节相关联,并且使用单独的神经网络来调整每个控制器的参数。神经网络被用来调节控制器的参数,作为神经网络的输出,控制参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robotic system based on neural network controllers

In this paper, a control algorithm based on neural networks is presented. This control algorithm has been applied to a robot arm which has a highly nonlinear structure. The model based approaches for robot control (such as the computed torque technique) require high computational time and can result in a poor control performance, if the specific model-structure selected does not properly reflect all the dynamics. The control technique proposed here has provided satisfactory results. A decentralised model has been assumed here where a controller is associated with each joint and a separate neural network is used to adjust the parameters of each controller. Neural networks have been used to adjust the parameters of the controllers, being the outputs of the neural networks, the control parameters.

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