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Robust adaptive output feedback tracking control for flexible-joint robot manipulators based on singularly perturbed decoupling

Published online by Cambridge University Press:  31 January 2018

Huashan Liu  and
Yong Huang
Huashan Liu*
Affiliation:
College of Information Science and Technology, Donghua University, Shanghai 201620, P.R. China
Yong Huang
Affiliation:
College of Information Science and Technology, Donghua University, Shanghai 201620, P.R. China
*
*Corresponding author. E-mails: hs.liu@qq.com, 1066994564@qq.com
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Summary

This paper presents a robust adaptive output feedback tracking controller for the flexible-joint robot manipulators to deal with the unknown upper bounds of parameter uncertainties and external disturbances. With applying the singular perturbation theory and integral manifold concept, the complex nonlinear coupled system of the flexible-joint robot manipulators is divided into a slow subsystem and a fast subsystem. A robust adaptive control scheme based on an improved linear parameterization expression is designed for the slow subsystem, and a saturation function is applied in the robust control term to make the torque output smooth. In the meantime, different from the previous approaches, the second-order derivative term of elastic torque is avoided by using the proposed computed torque method, which simplifies the implementation of the fast control law. Moreover, to carry out the whole control system with only position measurements, an approximate differential filter is involved to generate pseudo velocity signals for links and joint motors. In addition, an explicit but strict stability proof of the control system based on the theory of singularly perturbed systems is presented. Finally, simulation results verify the superior dynamic performance of the proposed controller.

Keywords

Flexible-joint robotRobust adaptive controlOutput feedback controlSingular perturbationApproximate differentiation
Type
Articles
Information
Robotica , Volume 36 , Issue 6 , June 2018 , pp. 822 - 838
Copyright
Copyright © Cambridge University Press 2018 

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