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Robust neural force control scheme under uncertainties in robot dynamics and unknown environment

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2 Author(s)
Seul Jung ; Dept. of Mechatronics Eng., Chung Nam Nat. Univ., Taejon, South Korea ; Hsia, T.C.

The original impedance function is known to lack robustness due to unknown robot dynamic model and the environment. In order to improve that result, a new impedance function is derived which specifies a desired force directly. This results in a new robust robot force tracking impedance control scheme, which employs a neural network as a compensator to cancel out all uncertainties. The proposed neural force control scheme is capable of making the robot track a specified desired force as well as of compensating for uncertainties in environment location and stiffness, and in robot dynamics. Separate training signals for free-space motion and contact-space motion control are developed to train the neural compensator online. The design of the training signals is justified. Simulation studies with a three-link rotary robot manipulator are carried out and the results show excellent force tracking performance

Published in:

Industrial Electronics, IEEE Transactions on  (Volume:47 ,  Issue: 2 )