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Impedance control with on-line neural-network compensator for robot contact tasks

โœ Scribed by Shih-Tin Lin; Jien-Shuin Lee

Publisher
Springer Netherlands
Year
1996
Tongue
English
Weight
442 KB
Volume
15
Category
Article
ISSN
0921-0296

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โœฆ Synopsis

In this paper, a force-tracking impedance controller with an on-line neural-network compensator is shown to be able to track a reference force in the presence of unknown environmental dynamics. The controller can be partitioned into three parts. The computed torque method is used to linearize and decouple the dynamics of a manipulator. An impedance controller is then added to regulate the mechanical impedance between the manipulator and its environment. In order to track a reference force signal, an on-line neural network is used to compensate the effect of unknown parameters of the manipulator and environment.

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โœ Chia-Ju Wu; Ching-Huo Huang ๐Ÿ“‚ Article ๐Ÿ“… 1996 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 633 KB

A simple and effective method for trajectory tracking of robotic manipulator is proposed. The first step is to employ a neural network to learn the characteristics of the inverse dynamics of the robotic manipulator in an off-line manner. Then the neural network is placed in series with the robotic m