2022
DOI: 10.3390/aerospace9110730
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Neural-Network-Based Terminal Sliding Mode Control of Space Robot Actuated by Control Moment Gyros

Abstract: This paper studies the trajectory tracking control of a space robot system (SRS) in the presence of the lumped uncertainties with no prior knowledge of their upper bound. Although some related control methods have been proposed, most of them have either not been applied to SRSs or lack rigorous stability proof. Therefore, it is still a challenge to achieve high accuracy and rigorous theoretical proof for tracking control of SRSs. This paper proposes a new integrated neural network- based control scheme for the… Show more

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Cited by 4 publications
(2 citation statements)
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“…SMC, known for its stability amidst noise and variable parameters, requires accurate model knowledge, which is complemented by RBFNN's ability to estimate nonlinear functions online. Additionally, fuzzy logic is proposed to mitigate oscillations around the sliding surface [15,16].…”
Section: Introductionmentioning
confidence: 99%
“…SMC, known for its stability amidst noise and variable parameters, requires accurate model knowledge, which is complemented by RBFNN's ability to estimate nonlinear functions online. Additionally, fuzzy logic is proposed to mitigate oscillations around the sliding surface [15,16].…”
Section: Introductionmentioning
confidence: 99%
“…However, the actual trajectory tracking and base disturbance are not reported through simulation results in this work. The issue of dynamic coupling and control of a space manipulator without an attitude controller was studied by Xia et al 29 Later, Liu et al 30 performed cooperative manipulation of a free-flying space robot using a new controller based on back-stepping and Lyapunov stability.…”
Section: Introductionmentioning
confidence: 99%