Model-Based Adaptive Control of Transfemoral Prostheses: Theory, Simulation, and Experiments

Azimi, Vahid; Shu, Tony; Zhao, Huihua; Gehlhar, Rachel; Simon, Dan; Ames, Aaron D.

doi:10.1109/tsmc.2019.2896193

Cited by 16 publications

(10 citation statements)

References 36 publications

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“…Azimi proposed an adaptive impedance controller to increase the robot's robustness to variations of ground reaction forces. They used a particle swarm optimizer (PSO) to find the optimal design parameters of the controller and the adaptation law [88]. Torabi et al proposed an admittance controller based on a nonlinear adaptive sliding mode scheme for a lower limb exoskeleton robot to provide robustness against disturbances while ensuring a compliant behavior during patient-exoskeleton interaction [89].…”

Section: Robotic Exoskeletonsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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Purpose of Review Research in assistive and rehabilitation robotics is a growing, promising, and challenging field emerged due to various social and medical needs such as aging populations, neuromuscular, and musculoskeletal disorders. Such robots can be used in various day-today scenarios or to support motor functionality, training, and rehabilitation. This paper reflects on the human-robot interaction perspective in rehabilitation and assistive robotics and reports on current issues and developments in the field. Recent Findings The survey on the literature reveals that new efforts are put on utilizing machine learning approaches alongside novel developments in sensing technology to adapt the systems with user routines in terms of activities for assistive systems and exercises for rehabilitation devices to fit each user's need and maximize their effectiveness. Summary A review of recent research and development efforts on human-robot interaction in assistive and rehabilitation robotics is presented in this paper. First, different subdomains in assistive and rehabilitation robotic research are identified, and accordingly, a survey on the background and trends of such developments is provided.

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Section: Robotic Exoskeletonsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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“…For example, Azimi et al (2018) presented ground reaction force estimation approaches to achieve model reference adaptive impedance control with consideration of parametric uncertainties and unmodeled dynamics. Azimi et al (2019) designed robust adaptive controllers for transfemoral prostheses, and then experimentally demonstrated the control schemes. A great deal of effort has been made for adaptive backstepping approaches, and by combining the backstepping control technique with fuzzy logic systems, neural networks approximation and sliding-mode control, many effective results have been obtained to cope with nonlinearity in uncertain systems.…”

Section: Introductionmentioning

confidence: 99%

Finite-time backstepping control with command filter for a class of nonlinear systems with parametric uncertainties

Feng

Wang

et al. 2020

Transactions of the Institute of Measurement and Control

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In this paper, the problem of adaptive finite-time control is considered for a class of nonlinear systems with parametric uncertainties. A novel adaptive command filtered backstepping control method is proposed, and the adverse impact caused by the command filter is eliminated by introducing modified error compensation mechanism with consideration of parametric uncertainties. Combined with the designed adaptation laws, the error compensation mechanism can be finite-time stable. Rigorous proof is achieved to show that the tracking error converges to a small neighborhood of zero in finite time with online parameters adaptation and error compensation. Finally, numeral simulations are presented to validate the effectiveness of the proposed adaptive finite-time control scheme.

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“…A robust adaptive control scheme (Le-Tien and Albu-Schäffer, 2017) based on a state feedback control method was designed for flexible-joint robots. A robust adaptive impedance scheme along with a sliding mode observer (Azimi et al, 2018) and a model-based adaptive control (Azimi et al, 2019) were applied successfully to control lower-limb prostheses. Designing two inner and outer control loops, indirect adaptive Taylor series controllers (Haqshenas M. et al, 2020) were proposed for electrically driven WMRs.…”

Section: Introductionmentioning

confidence: 99%

A state augmented adaptive backstepping control of wheeled mobile robots

Ahmadi

Taghadosi

2020

Transactions of the Institute of Measurement and Control

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The present paper aims to design an integrated kinematic/dynamic-based tracking controller for wheeled mobile robots (WMRs) considering motors’ dynamics. By defining a reference WMR, the role of kinematic controller is to not only minimize the posture error which indicates the difference between the reference and actual WMRs, but also to generate a desired path for the actual WMR. The kinematic tracking control problem of WMRs is so challenging if motors’ dynamics, parametric and nonparametric uncertainties and external disturbances are considered. Thus, proposing a dynamic control law alongside a kinematic control is unavoidable. In this study, we propose a new dynamic controller, namely, a state augmented adaptive backstepping such that the desired path is asymptotically tracked. Several numerical results accompanied by 3D simulations of trajectory tracking control of a WMR in ‘Simscape Multibody’ environment and comparisons with two well-designed controllers in the literature are reported to show the high performance of proposed control structure.

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Model-Based Adaptive Control of Transfemoral Prostheses: Theory, Simulation, and Experiments

Cited by 16 publications

References 36 publications

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Finite-time backstepping control with command filter for a class of nonlinear systems with parametric uncertainties

A state augmented adaptive backstepping control of wheeled mobile robots

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