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Finite-time tracking control for uncertain robotic manipulators using backstepping method and novel extended state observer

Chao Chen, Chengrui Zhang, Tianliang Hu, Hepeng Ni, Qizhi Chen

Year
2019
Citations
27
Access
Open access

Abstract

This article considers finite-time trajectory tracking control problem for robotic manipulators with parameter uncertainties and external disturbances. A finite-time controller that achieves high precision and strong robustness is proposed without the requirement of the exact dynamic model. First, a novel finite-time model-assisted extended state observer is designed to compensate the system uncertainties with complex and uncertain dynamics. Then, a composite finite-time controller is developed for trajectory tracking control with the help of finite-time model-assisted extended state observer. Compared to the classic extended state observer, it is proved that the estimation error of finite-time model-assisted extended state observer can be stabilized in finite time. Meanwhile, the finite-time convergence of the closed-loop system with the proposed controller can also be proved through Lyapunov’s stability theory. A variable structure term is employed to compensate the estimation errors of finite-time model-assisted extended state observer. The validity of the control scheme is demonstrated by simulations and experiments.

Keywords

Control theory (sociology)Computer scienceBacksteppingRobustness (evolution)Observer (physics)TrajectoryState observerController (irrigation)Convergence (economics)Lyapunov function

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