Robust approximate constraint following control for SCARA robots system with uncertainty and experimental validation

Zhen, Shengchao; Chun-lin, Meng; Xiao, Haowen; Liu, Xiaoli; Chen, Ye‐Hwa

doi:10.1016/j.conengprac.2023.105610

Cited by 6 publications

(1 citation statement)

References 34 publications

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“…However, PID controllers do not meet the high-precision control requirements of robot systems with nonlinear and time-varying characteristics. In [11,12], a robust control method was introduced into the nonlinear mechanical system of constrained robots, but [12] can only guarantee that the time-varying bounded constraints were satisfied. To achieve accuracy in tracking the position of human hands, an adaptive impedance control was proposed by combining nonlinear control theory with dynamic models to guarantee the safety of human-robot interaction [13].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neural Network Tracking Control of Robotic Manipulators Based on Disturbance Observer

Li,

Zhang,

Zhang

et al. 2024

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This article presents an adaptive neural network (ANN) control scheme based on a disturbance observer that can achieve trajectory tracking control of robotic manipulators under external disturbances and dynamic model uncertainties. Firstly, an ANN controller based on full-state feedback is derived using the backstepping technique to achieve an online approximation of uncertainty. The integral sliding mode surface with a position error is introduced into the controller, which reduces the steady-state error of the system and enhances robustness. Then, a novel disturbance observer is designed to estimate both the approximation errors of the ANN and external disturbances, and to provide compensation for the controller, effectively suppressing the trajectory tracking errors caused by approximation errors and disturbances. Subsequently, the Lyapunov stability theory is utilized to demonstrate the stability of the developed control strategy and the boundedness of all closed-loop signals. Finally, numerical simulations are used to confirm the efficacy of the proposed control method.

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