An iterative learning scheme for motion control of robots using neural networks: A case study |
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Authors: | Jianguo Fu Naresh K Sinha |
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Affiliation: | (1) Department of Electrical and Computer Engineering, McMaster University, L8S 4L7 Hamilton, Ontario, Canada |
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Abstract: | In this paper, an iterative learning controller using neural networks has been studied for the motion control of robotic manipulators. Simulations of a two-link robot have demonstrated that the proposed control scheme for robotic manipulators can greatly reduce tracking errors after a few trials. Our modification of the original back-propagation algorithm is employed in the neural network, resulting in a much faster learning rate. The results of simulation have also shown that the proposed iterative learning controller has a faster rate of convergence and better robustness. |
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Keywords: | Learning control back-propagation neural network motion control of robot |
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