Wilson, E.D., Assaf, T., Pearson, M.J. et al. (4 more authors) (2016) Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle. Interface, 13 (122). ISSN 1742-5689
Abstract
Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
Keywords: | adaptive-inverse control; artificial muscle; cerebellum; nonlinear control; soft robotics; transfer of training |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 26 Sep 2016 14:43 |
Last Modified: | 27 Jan 2020 14:04 |
Published Version: | http://dx.doi.org/10.1098/rsif.2016.0547 |
Status: | Published |
Publisher: | Royal Society, The |
Refereed: | Yes |
Identification Number: | 10.1098/rsif.2016.0547 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:105234 |