Robust neural force control scheme under uncertainties in robotdynamics and unknown environment
Seul Jung
Hsia, T.C.
Dept. of Mechatronics Eng., Chung Nam Nat. Univ., Taejon;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Apr 2000
Volume: 47,
Issue: 2
On page(s): 403-412
ISSN: 0278-0046
References Cited: 19
CODEN: ITIED6
INSPEC Accession Number: 6573379
Digital Object Identifier: 10.1109/41.836356
Current Version Published: 2002-08-06
Abstract
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
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