2020
DOI: 10.1109/access.2020.3030805
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Robust Adaptive Finite-Time Tracking Control for Uncertain Euler-Lagrange Systems With Input Saturation

Abstract: In this paper, a robust adaptive finite-time (FT) tracking control scheme is proposed for Euler-Lagrange systems (ELSs) subject to nonparametric uncertainties, unknown disturbances and input saturation. In the design procedure, a Gaussian error function is utilized to approximate the input saturation nonlinearity. Following that, by employing the natural property that the upper bound of model parameters uncertainties is linear-in-parameters, the lumped uncertain term that caused by uncertain model parameters a… Show more

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Cited by 5 publications
(8 citation statements)
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“…􏼣 e e d 􏼢 􏼣, (22) where Ω 1 � − PΨ − Ψ T P + Q + dΨ T PR − 1 PΨ and Ω 2 � − 􏽥 μQ + dΨ T RΨ. From Lemma 3, _ V s is negative if (16) holds.…”
Section: Stability Of Sliding Motionmentioning
confidence: 99%
See 1 more Smart Citation
“…􏼣 e e d 􏼢 􏼣, (22) where Ω 1 � − PΨ − Ψ T P + Q + dΨ T PR − 1 PΨ and Ω 2 � − 􏽥 μQ + dΨ T RΨ. From Lemma 3, _ V s is negative if (16) holds.…”
Section: Stability Of Sliding Motionmentioning
confidence: 99%
“…e model-free optimal consensus problem was addressed for networked Euler-Lagrange systems without velocity measurements [21]. Chen et al proposed a robust adaptive finite-time tracking control scheme for Euler-Lagrange systems subject to nonparametric uncertainties, unknown disturbances, and input saturation [22]. In [23], a robust adaptive finite-time tracking control scheme was proposed for Euler-Lagrange systems subject to nonparametric uncertainties, unknown disturbances, and input saturation.…”
Section: Introductionmentioning
confidence: 99%
“…For the uncertain ELSs with parameterized decomposition conditions, the adaptive control schemes [11]- [15], especially the adaptive sliding mode control (SMC) schemes [16]- [17], were proposed to ensure the tracking error asymptotical or exponential convergence. In [18], the the tracking error asymptotical convergence was also achieved by a recursive robust integral of the sign of the error control method for mechanical servosystems with mismatched uncertainties.…”
Section: Introductionmentioning
confidence: 99%
“…In [18], the the tracking error asymptotical convergence was also achieved by a recursive robust integral of the sign of the error control method for mechanical servosystems with mismatched uncertainties. In contrast, when the nonparametric uncertainties and external disturbances exist in the ELSs, the control methods mentioned in [11]- [17] are inapplicable. In this context, combining neural network (NN) with adaptive technique, the neuroadaptive control schemes were developed for uncertain robotic manipulators neglecting external disturbances and the issue of operational space constraint [19]- [20].…”
Section: Introductionmentioning
confidence: 99%
“…Generally, when a system works under uncertain disturbances, we need to improve the robustness of the control as much as possible. Some scholars have studied the trajectory tracking method of EL systems; the common methods include the backstepping technique [8], dynamics surface control (DSC) [9], robust control [10,11], adaptive control [12,13], sliding mode control [14], and learning control [15]. Among them, the error restriction method can effectively enhance the robustness of the control.…”
Section: Introductionmentioning
confidence: 99%