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Robust control of electrically driven robots using adaptive uncertainty estimation
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DOI：10.1016/j.compeleceng.2016.08.005.png)
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This paper presents a novel robust control for electrically driven robot manipulators by designing an adaptive uncertainty estimator based on the first order Taylor series. The estimator is simple and model-free in a decentralized structure. The uncertainty is then efficiently compensated in the control system. The controller does not require the bounding functions as an advantage over the conventional robust controller. Therefore, it is simpler, less computational, and more efficient. It is verified by stability analysis and its effectiveness is shown through comparisons with a terminal sliding mode control approach and a Legendre polynomials uncertainty bound estimator simulated on a SCARA robot driven by permanent magnet dc motors. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Adaptive uncertainty estimation
Robust control
Taylor series
Electrically driven robot manipulators
SCARA robot
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