基于神经网络的任务空间机器人跟踪

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) Pub Date : 1994-06-27 DOI:10.1109/ICNN.1994.374684

G. Feng, C. K. Chak

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引用次数: 18

摘要

研究了机器人在任务空间中的跟踪控制问题。提出了一种基于传统控制器和基于神经网络的补偿控制器的新型控制方案。该方案利用基于模型的控制方法的简单性，利用神经网络控制器对机器人建模的不确定性进行补偿。基于李雅普诺夫理论对神经网络进行在线训练，保证了神经网络的收敛性。

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Robot tracking in task space using neural networks

This paper considers tracking control of robots in task space. A new control scheme is proposed based on a kind of conventional controller and a neural network based compensating controller. This scheme takes advantages of simplicity of the model based control approach and uses the neural network controller to compensate for the robot modelling uncertainties. The neural network is trained online based on Lyapunov theory and thus its convergence is guaranteed.<>

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Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

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