Disturbance observer‐based adaptive boundary iterative learning control for a rigid‐flexible manipulator with input backlash and endpoint constraint - Archive ouverte HAL Access content directly
Journal Articles International Journal of Adaptive Control and Signal Processing Year : 2020

Disturbance observer‐based adaptive boundary iterative learning control for a rigid‐flexible manipulator with input backlash and endpoint constraint

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Haoping Wang
Yang Tian
Gang Zheng

Abstract

In this article, an observer‐based adaptive boundary iterative learning control law is developed for a class of two‐link rigid‐flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the adaptive boundary control design. A barrier Lyapunov function is incorporated with boundary control law to restrict the endpoint state. Based on the defined barrier composite energy function, the tracking angle error convergence of the rigid part is guaranteed, and the vibrations of the flexible part are suppressed through the rigorous analysis. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed control.
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Dates and versions

hal-03087577 , version 1 (23-12-2020)

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Cite

Xingyu Zhou, Haoping Wang, Yang Tian, Gang Zheng. Disturbance observer‐based adaptive boundary iterative learning control for a rigid‐flexible manipulator with input backlash and endpoint constraint. International Journal of Adaptive Control and Signal Processing, 2020, 34 (9), pp.1220-1241. ⟨10.1002/acs.3150⟩. ⟨hal-03087577⟩
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