Journal of Intelligent and Robotic Systems

, Volume 8, Issue 3, pp 375–398 | Cite as

An iterative learning scheme for motion control of robots using neural networks: A case study

  • Jianguo Fu
  • Naresh K. Sinha
Article

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.

Key words

Learning control back-propagation neural network motion control of robot 

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Copyright information

© Kluwer Academic Publishers 1993

Authors and Affiliations

  • Jianguo Fu
    • 1
  • Naresh K. Sinha
    • 1
  1. 1.Department of Electrical and Computer EngineeringMcMaster UniversityHamiltonCanada

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