Application of the optimal homotopy asymptotic method to nonlinear Bingham fluid dampers

Marinca, Vasile; Ene, Remus-Daniel; Bereteu, Liviu

doi:10.1515/phys-2017-0072

Cited by 2 publications

(1 citation statement)

References 38 publications

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“…The Bingham model is a linear variant of the Herschel–Bulkley model, as may be seen, that is, when m = 1 . Even if the Herschel–Bulkley model represents the behavior of the MRF accurately, the Bingham plastic model is mostly used since it is straightforward ( Marinca et al, 2017 ).…”

Section: Modeling the Mr Dampermentioning

confidence: 99%

Design of a Super Twisting Sliding Mode Controller for an MR Damper-Based Semi-Active Prosthetic Knee

Assfaw

Seid

2022

Front. Robot. AI

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A large number of transfemoral amputees living in low-income countries could not access a much-needed prosthesis. Hence, affordable semi-active prosthetic knees have been designed in recent years. As the swing phase of the gait cycle is unstable as compared to the stance phase, these designs could not perfectly mimic this phase of a healthy human being. In contribution toward such a gap, this study proposes the modeling and design of a robust controller for magnetorheological (MR) damper-based semi-active prosthetic knee. A dynamic model representation for the swing phase of the single-axis knee is derived first. Subsequently, an MR damper valve model is developed. Then, a higher-order sliding mode controller is designed and evaluated for its stability and performance. The numerical simulation results show that the super twisting sliding mode controller improves the semi-active prosthetic knee’s tracking efficiency. The design exhibited the finest performance, providing a low normalized mean square error as compared to previous designs. The variable speed performance and robustness evaluation for this controller also showed its ability to continue providing excellent performance in the presence of disturbances.

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Section: Modeling the Mr Dampermentioning

confidence: 99%

Design of a Super Twisting Sliding Mode Controller for an MR Damper-Based Semi-Active Prosthetic Knee

Assfaw

Seid

2022

Front. Robot. AI

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A Deep Neural Network Based Model for a Kind of Magnetorheological Dampers

Duchanoy

Moreno-Armendáriz

Moreno-Torres

et al. 2019

Sensors

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In this paper, a deep neural network based model for a set of small-scale magnetorheological dampers (MRD) is developed where relevant parameters that have a physical meaning are inputs to the model. An experimental platform and a 3D-printing rapid prototyping facility provided a set of different conditions including MRD filled with two different MR fluids, which were used to train a Deep Neural Network (DNN), which is the core of the proposed model. Testing results indicate the model could forecast the hysteretic response of magnetorheological dampers for different load conditions and various physical configurations.

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Application of the optimal homotopy asymptotic method to nonlinear Bingham fluid dampers

Cited by 2 publications

References 38 publications

Design of a Super Twisting Sliding Mode Controller for an MR Damper-Based Semi-Active Prosthetic Knee

Design of a Super Twisting Sliding Mode Controller for an MR Damper-Based Semi-Active Prosthetic Knee

A Deep Neural Network Based Model for a Kind of Magnetorheological Dampers

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