Nonlinear disturbance observer-based robust predefined time tracking and vibration suppression control for the rigid-flexible coupled robotic mechanisms with large beam-deformations

Zhou, Xingyu; Wang, Haoping; Wu, Ke; Tian, Yang; Zheng, Gang

doi:10.1016/j.camwa.2023.08.003

Cited by 2 publications

(2 citation statements)

References 38 publications

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“…In order to solve the issue of system uncertainties, scholars have proposed many effective attempts [18][19][20][21][22][23][24][25]. There are currently two main types of algorithms: (1) neural network-based approximation algorithms; and (2) disturbance observer-based algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…In ref. [22], a nonlinear disturbance observer is developed to address the system uncertainties of the robotic arm. Although the observer is capable of providing precise estimations of the system uncertainties, it can only achieve an asymptotically stable tracking performance, which means that the optimal convergence speed of the system is exponentially convergent, and the tracking error can converge to zero in infinite time.…”

Section: Introductionmentioning

confidence: 99%

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Fixed-Time Control of a Robotic Arm Based on Disturbance Observer Compensation

Zhang,

Pan,

et al. 2023

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Backstepping-based fixed-time tracking control is proposed for a robotic arm system to solve the problem of trajectory tracking control under system uncertainties, which ensures the robotic arm system can realize stable tracking control within a fixed time independent of the initial state of the system. In addition, to address the uncertainties in the robotic arm system, a control strategy based on disturbance observer compensation is designed, which provides feed-forward compensation through the accurate estimation of the system uncertainties and enhances the system’s robustness. Finally, a two-link robotic arm model is used for simulation experiments, and the comparison results show that the control scheme designed in this article can effectively improve the robotic arm’s tracking accuracy and convergence speed.

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