An Improved Super-Twisting Sliding Mode for Flexible Upper-Limb Exoskeleton

Zhang, Saihua; Zhang, Xinghua; Sun, Zhenxing

doi:10.3390/act12010032

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…Conventional control systems are proven to be efficient enough to handle typical applications of electric drives, e.g., cooling fans, air conditioners, etc. However, consistent extension of possible electric drive applications, such as wind turbines [2,3], robotic manipulators [4][5][6][7], and exoskeletons [8,9], often implicates the necessity of handling a sophisticated and complex mechanical structure. One of the possible reasons for potential problems is related to lighter mechanical construction, which gives the structure more flexibility [10].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control Based on a Radial Neural Model Applied for an Electric Drive with an Elastic Shaft

Kaczmarczyk,

Stanislawski,

Szrek

et al. 2024

Energies

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External disturbances, uncertainties, and nonlinear behavior are problems that are commonly encountered by control system designers. In order to save on energy and materials, mechanical structures have become lighter and more flexible, which only exacerbates the control problem. To resolve this issue, robust and adaptive control strategies have been proposed and have recently gained a lot of interest in modern scientific literature. This article proposes a combination of both approaches: a sliding mode—radial basis function neural network controller applied to an electrical drive with a sophisticated mechanical structure. The proposed sliding surface provides robustness against parameter uncertainties, while the neural network adjusts itself to the current state of the drive and mitigates the oscillations resulting from the elastic connection with the load machine. This article proves the stability of the proposed control algorithm in the sense of Lyapunov, provides an in-depth numerical analysis, and compares those results with the experimental tests. The algorithm was implemented in a 1103 dSPACE fast-prototyping card and was used to control a 0.5 kW DC motor connected to the load machine by a long (thin) steel shaft.

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Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control Based on a Radial Neural Model Applied for an Electric Drive with an Elastic Shaft

Kaczmarczyk,

Stanislawski,

Szrek

et al. 2024

Energies

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Control Method of Upper Limb Rehabilitation Exoskeleton for Better Assistance: A Comprehensive Review

Wang,

Ren,

et al. 2024

Journal of Field Robotics

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The upper limb rehabilitation exoskeleton is a robotic‐arm‐like device that fits the human upper limb and assists in movement, having the potential to be widely used in medical practice. The control method of the upper limb rehabilitation exoskeleton system is an important factor that affects the effectiveness of its rehabilitation training assistance and is also the focus of research in this field. In this article, we divide the control method of the upper limb rehabilitation exoskeleton into two levels, the high‐level control mode (including passive mode, active mode, and ANN, etc.) and the low‐level controller. The design of the controller aims to meet the requirements of the control mode but faces difficulties such as complex dynamic models of the system, unknown external disturbances, and motion intention recognition to achieve accurate motion trajectory tracking and flexible human–robot interaction. Based on relevant literature in the field of upper limb rehabilitation exoskeleton control methods in recent years, we analyze the rehabilitation training control modes that researchers aim to achieve, as well as the work they have done in controller design to achieve these control modes. We also propose potential research directions for achieving better exoskeleton‐assisted training effects.

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An Improved Super-Twisting Sliding Mode for Flexible Upper-Limb Exoskeleton

Cited by 2 publications

References 22 publications

Adaptive Sliding Mode Control Based on a Radial Neural Model Applied for an Electric Drive with an Elastic Shaft

Adaptive Sliding Mode Control Based on a Radial Neural Model Applied for an Electric Drive with an Elastic Shaft

Control Method of Upper Limb Rehabilitation Exoskeleton for Better Assistance: A Comprehensive Review

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