Model-based feedforward and cascade control of hydraulic McKibben muscles

Meller, Michael; Kogan, B. L.; Bryant, Matthew; Garcia, Ephrahim

doi:10.1016/j.sna.2018.03.036

Cited by 17 publications

(13 citation statements)

References 33 publications

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Section: Modelingmentioning

confidence: 99%

“…These designs are currently unable to be reduced to an exact model which often leads to rigid-body assumptions to create manageable dynamic equations [121]. Figure 10 below shows a McKibben muscle controlling a rigid body mechanism, allowing for the deformation of the actuator to be easily measured with rigid body dynamic equations [122]. Recently, sets of ordinary differential equations have been formulated to create a more mathematically accurate model to describe the dynamic motion of soft robotics [119].…”

Section: Modelingmentioning

confidence: 99%

mentioning

confidence: 99%

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Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators

et al. 2020

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This paper focuses on the recent development of soft pneumatic actuators for soft robotics over the past few years, concentrating on the following four categories: control systems, material and construction, modeling, and sensors. This review work seeks to provide an accelerated entrance to new researchers in the field to encourage research and innovation. Advances in methods to accurately model soft robotic actuators have been researched, optimizing and making numerous soft robotic designs applicable to medical, manufacturing, and electronics applications. Multi-material 3D printed and fiber optic soft pneumatic actuators have been developed, which will allow for more accurate positioning and tactile feedback for soft robotic systems. Also, a variety of research teams have made improvements to soft robot control systems to utilize soft pneumatic actuators to allow for operations to move more effectively. This review work provides an accessible repository of recent information and comparisons between similar works. Future issues facing soft robotic actuators include portable and flexible power supplies, circuit boards, and drive components.

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Section: Modelingmentioning

confidence: 99%

Section: Modelingmentioning

confidence: 99%

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Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators

et al. 2020

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“…While the model derived above provides a predictive and qualitatively reasonable analysis for understanding the implications of resistive forces on variable recruitment bundles, the model can be empirically corrected to improve quantitative agreement with experimental FAM characterization data. Such semi-empirical modeling has been shown to useful for model-based feedforward control of artificial muscles [34], and in simulation tools for understanding the implications of different recruitment strategies [10] or hydraulic system topologies [15] on FAM actuation systems. Therefore, to further improve the model to match the force from experiments, a method of force correction was developed.…”

Section: Improving the Model Through Empirical Parameter Tuningmentioning

confidence: 99%

Modeling of Resistive Forces and Buckling Behavior in Variable Recruitment Fluidic Artificial Muscle Bundles

2021

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Fluidic artificial muscles (FAMs), also known as McKibben actuators, are a class of fiber-reinforced soft actuators that can be pneumatically or hydraulically pressurized to produce muscle-like contraction and force generation. When multiple FAMs are bundled together in parallel and selectively pressurized, they can act as a multi-chambered actuator with bioinspired variable recruitment capability. The variable recruitment bundle consists of motor units (MUs)—groups of one of more FAMs—that are independently pressurized depending on the force demand, similar to how groups of muscle fibers are sequentially recruited in biological muscles. As the active FAMs contract, the inactive/low-pressure units are compressed, causing them to buckle outward, which increases the spatial envelope of the actuator. Additionally, a FAM compressed past its individual free strain applies a force that opposes the overall force output of active FAMs. In this paper, we propose a model to quantify this resistive force observed in inactive and low-pressure FAMs and study its implications on the performance of a variable recruitment bundle. The resistive force behavior is divided into post-buckling and post-collapse regions and a piecewise model is devised. An empirically-based correction method is proposed to improve the model to fit experimental data. Analysis of a bundle with resistive effects reveals a phenomenon, unique to variable recruitment bundles, defined as free strain gradient reversal.

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“…There has been little reported on the modeling and control of HAMs. Meller et al reported the results of feedforward position control based on an empirical model [12].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Impedance Control of a Hydraulic Artificial Muscle

Slightam

Nagurka

Barth

2018

Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation

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Hydraulic artificial muscles offer unrivaled specific power and power density and are instrumental to the improved performance and success of soft robotics and lightweight mobile applications. This paper addresses the lack of model-based impedance control approaches for soft actuators such as hydraulic artificial muscles. Impedance control of actuators and robotic systems has been proven to be an effective approach for interacting with physical objects in the presence of uncertainty. A sliding mode impedance control approach based on Filippov’s principle of equivalent dynamics is introduced and applied to a hydraulic artificial muscle. A nonlinear lumped parameter model of the system is presented and a sliding mode impedance controller is derived. Experimental results show superior performance using model-based sliding mode impedance control versus a linear impedance control law in both tracking of position and stiffness when disturbances are introduced.

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Model-based feedforward and cascade control of hydraulic McKibben muscles

Cited by 17 publications

References 33 publications

Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators

Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators

Modeling of Resistive Forces and Buckling Behavior in Variable Recruitment Fluidic Artificial Muscle Bundles

Sliding Mode Impedance Control of a Hydraulic Artificial Muscle

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