Robust Adaptive Control of Knee Exoskeleton-Assistant System Based on Nonlinear Disturbance Observer

Aljuboury, Anwer S.; Hameed, Aisha; Ajel, Ahmed R.; Humaidi, Amjad J.; Alkhayyat, Ahmed; Mhdawi, Ammar K. Al

doi:10.3390/act11030078

Cited by 25 publications

(11 citation statements)

References 25 publications

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“…The Exoskeleton Knee system is a wearable robotic device that is used to restore or enhance the function of the lower limb (Shawgi et al, 2022;Alawad et al, 2022). Figure 1 depicts the geometric representation of leg motion at the knee joint (Aljuboury et al, 2022). According to Figure 1., the parameters 𝑚 and 𝑙 are the mass and length of the shank, respectively, while 𝑔 is the gravitational acceleration.…”

Section: Modelling Of Exoskeleton System For Lower-limbmentioning

confidence: 99%

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Active Disturbance Rejection Control of Wearable Lower-Limb System Based on Reduced ESO

Alawad

Humaidi

Al-Obaidi

et al. 2022

Indonesian J. Sci. Technol

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Wearable robots are commonly used for rehabilitation and they are made to fit the human body to assist persons who are unable to help themselves. The design of controllers became necessary to enhance the dynamic motion of these exoskeleton systems when worn by patients. In this study, active disturbance rejection control (ADRC) with reduced-order extended state observer (RESO) has been proposed for motion control of exoskeleton knee-assisting device to eliminate the phase lag induced by full-order extended state observer (FESO). The design analysis of RESO-based ADRC has been presented and a computer simulation has been conducted to verify the effectiveness of the proposed controller. A comparison study has been made between ADRC based on RESO and that based on FESO in terms of transient and robustness characteristics. The simulated results showed that the RESO-based ADRC gives better transient and load rejection capabilities compared to the controller with FESO.

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Section: Modelling Of Exoskeleton System For Lower-limbmentioning

confidence: 99%

“…The nonlinear dynamic for the exoskeleton and human model with one joint, at the knee, is determined through the use of the Euler-Lagrange method. The dynamic modelling of the system can be expressed as follows (Aljuboury et al, 2022;Bkekri et al, 2019;Mefoued,2015) (see Equation ( 1)):…”

Section: Modelling Of Exoskeleton System For Lower-limbmentioning

confidence: 99%

Active Disturbance Rejection Control of Wearable Lower-Limb System Based on Reduced ESO

Alawad

Humaidi

Al-Obaidi

et al. 2022

Indonesian J. Sci. Technol

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“…The accuracy of gait tracking of exoskeleton system is considerably enhanced and the follow-up performance has been greatly improved. In [24], Aljuboury et al presented the design of three control schemes based on model reference adaptive control (MRAC) for an exoskeleton knee assistance system. This study showed that the observer-based MRAC outperformed the classical MRAC and adaptive MRAC in terms of robustness characteristics and tracking accuracy.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Synergetic Motion Control for Wearable Knee-Assistive System: A Rehabilitation of Disabled Patients

et al. 2022

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In this study, synergetic-based adaptive control design is developed for trajectory tracking control of joint position in knee-rehabilitation system. This system is often utilized for rehabilitation of patients with lower-limb disabilities. However, this knee-assistive system is subject to uncertainties when applied to different persons undertaking exercises. This is due to the different masses and inertias of different persons. In order to cope with these uncertainties, an adaptive scheme has been proposed. In this study, an adaptive synergetic control scheme is established, and control laws are developed to ensure stable knee exoskeleton system subjected to uncertainties in parameters. Based on Lyapunov stability analysis, the developed adaptive synergetic laws are used to estimate the potential uncertainties in the coefficients of the knee-assistive system. These developed control laws guarantee the stability of the knee rehabilitation system controlled by the adaptive synergetic controller. In this study, particle swarm optimization (PSO) algorithm is introduced to tune the design parameters of adaptive and non-adaptive synergetic controllers, in order to optimize their tracking performances by minimizing an error-cost function. Numerical simulations are conducted to show the effectiveness of the proposed synergetic controllers for tracking control of the exoskeleton knee system. The results show that compared to classical synergetic controllers, the adaptive synergetic controller can guarantee the boundedness of the estimated parameters and hence avoid drifting, which in turn ensures the stability of the controlled system in the presence of parameter uncertainties.

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“…A new control strategy (ADRC) has been used recently to cancel these effects due to the impact of internal and external disturbances on the position trajectory of the Exoskeleton system [9][10][11]. There are numerous ways to build an ADRC, both linear and nonlinear, and the feed-forward controller may use a variety of techniques, including fuzzy control, artificial intelligence control, classical PD, and fractional PD [11][12][13][14][15]. Each of these approaches has benefits and drawbacks in terms of performance robustness against rejection disturbances.…”

Section: Introductionmentioning

confidence: 99%

Observer Sliding Mode Control Design for lower Exoskeleton system: Rehabilitation Case

Alawad¹,

Humaidi²,

Al-Araji³

2022

Journal of Robotics and Control

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Sliding mode (SM) has been selected as the controlling technique, and the state observer (SO) design is used as a component of active disturbance rejection control (ADRC) to reduce the knee position trajectory for therapeutic purposes. The suggested controller will improve the needed position performances for the Exoskeleton system when compared to the proportional-derivative controller (PD) and SMC as feed-forward in the ADRC approach, as shown theoretically and through computer simulations. Simulink tool is used in this comparison to analyze the nominal case and several disruption cases. The results of mathematical modeling and simulation studies demonstrated that SMC with a disturbance observer strategy performs better than the PD control system and SMC in feed-forward with a greater capacity to reject disturbances and significantly better than these controllers. Performance indices are used for numerical comparison to demonstrate the superiority of these controllers.

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Robust Adaptive Control of Knee Exoskeleton-Assistant System Based on Nonlinear Disturbance Observer

Cited by 25 publications

References 25 publications

Active Disturbance Rejection Control of Wearable Lower-Limb System Based on Reduced ESO

Active Disturbance Rejection Control of Wearable Lower-Limb System Based on Reduced ESO

Adaptive Synergetic Motion Control for Wearable Knee-Assistive System: A Rehabilitation of Disabled Patients

Observer Sliding Mode Control Design for lower Exoskeleton system: Rehabilitation Case

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