Learning control of robotic manipulators

Heng-Ming Tai; Yu-Che Chen

doi:10.1117/12.140034

16 September 1992 Learning control of robotic manipulators

Heng-Ming Tai, Yu-Che Chen

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140034
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

In this paper, we propose a learning control scheme for direct trajectory control of robotic manipulators. The main features are that we use a priori structure knowledge of robot dynamics in the design and the neural networks are not used to learn inverse dynamic models. The neural network controller is utilized to compensate the deviation due to the approximate models of robotic manipulators. In addition, true teaching signals of the neural network compensators are employed in the learning phase. Simulations are conducted to show the feasibility of the proposed method.

Citation Download Citation

Heng-Ming Tai and Yu-Che Chen "Learning control of robotic manipulators", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140034

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