Dataset Information

Closed-Loop Control of Electro-Ribbon Actuators.

ABSTRACT: Electro-ribbon actuators are lightweight, flexible, high-performance actuators for next generation soft robotics. When electrically charged, electrostatic forces cause the electrode ribbons to progressively zip together through a process called dielectrophoretic liquid zipping (DLZ), delivering contractions of more than 99% of their length. Electro-ribbon actuators exhibit pull-in instability, and this phenomenon makes them challenging to control: below the pull-in voltage threshold, actuator contraction is small, while above this threshold, increasing electrostatic forces cause the actuator to completely contract, providing a narrow contraction range for feedforward control. We show that application of a time-varying voltage profile that starts above pull-in threshold, but subsequently reduces, allows access to intermediate steady-states not accessible using traditional feed-forward control. A modified proportional-integral closed-loop controller is proposed (Boost-PI), which incorporates a variable boost voltage to temporarily elevate actuation close to, but not exceeding, the pull-in voltage threshold. This primes the actuator for zipping and drastically reduces rise time compared with a traditional PI controller. A multi-objective parameter-space approach was implemented to choose appropriate controller gains by assessing the metrics of rise time, overshoot, steady-state error, and settle time. This proposed control method addresses a key limitation of the electro-ribbon actuators, allowing the actuator to perform staircase and oscillatory control tasks. This significantly increases the range of applications which can exploit this new DLZ actuation technology.

SUBMITTER: Diteesawat RS

PROVIDER: S-EPMC7805931 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Closed-Loop Control of Electro-Ribbon Actuators.

Diteesawat Richard Suphapol RS Fishman Aaron A Helps Tim T Taghavi Majid M Rossiter Jonathan J

Frontiers in robotics and AI 20201116

Electro-ribbon actuators are lightweight, flexible, high-performance actuators for next generation soft robotics. When electrically charged, electrostatic forces cause the electrode ribbons to progressively zip together through a process called dielectrophoretic liquid zipping (DLZ), delivering contractions of more than 99% of their length. Electro-ribbon actuators exhibit pull-in instability, and this phenomenon makes them challenging to control: below the pull-in voltage threshold, actuator co ...[more]

PMID: 33501320

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Project description:A neuroprosthesis using a brain-machine interface (BMI) is a promising therapeutic option for severely paralyzed patients, but the ability to control it may vary among individual patients and needs to be evaluated before any invasive procedure is undertaken. We have developed a neuroprosthetic hand that can be controlled by magnetoencephalographic (MEG) signals to noninvasively evaluate subjects' ability to control a neuroprosthesis.Six nonparalyzed subjects performed grasping or opening movements of their right hand while the slow components of the MEG signals (SMFs) were recorded in an open-loop condition. The SMFs were used to train two decoders to infer the timing and types of movement by support vector machine and Gaussian process regression. The SMFs were also used to calculate estimated slow cortical potentials (eSCPs) to identify the origin of motor information. Finally, using the trained decoders, the subjects controlled a neuroprosthetic hand in a closed-loop condition.The SMFs in the open-loop condition revealed movement-related cortical field characteristics and successfully inferred the movement type with an accuracy of 75.0 ± 12.9% (mean ± SD). In particular, the eSCPs in the sensorimotor cortex contralateral to the moved hand varied significantly enough among the movement types to be decoded with an accuracy of 76.5 ± 10.6%, which was significantly higher than the accuracy associated with eSCPs in the ipsilateral sensorimotor cortex (58.1 ± 13.7%; p = 0.0072, paired two-tailed Student's t-test). Moreover, another decoder using SMFs successfully inferred when the accuracy was the greatest. Combining these two decoders allowed the neuroprosthetic hand to be controlled in a closed-loop condition.Use of real-time MEG signals was shown to successfully control the neuroprosthetic hand. The developed system may be useful for evaluating movement-related slow cortical potentials of severely paralyzed patients to predict the efficacy of invasive BMI.

Dataset Information

Closed-Loop Control of Electro-Ribbon Actuators.

Publications

Closed-Loop Control of Electro-Ribbon Actuators.

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