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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Fu, J., Sinha, N.K. An iterative learning scheme for motion control of robots using neural networks: A case study. J Intell Robot Syst 8, 375–398 (1993). https://doi.org/10.1007/BF01257950
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DOI: https://doi.org/10.1007/BF01257950