An Extended State Observer Based Super-Twisting Sliding Mode Controller for Electrostatic Actuators

This paper presents a super twisting sliding mode control (STSMC) system to stabilize a parallel-plate electrostatic actuator (ESA) and extend its operating range beyond the pull-in point. A voltage-controlled ESA is stable only within one-third of the full gap due to susceptibility to pull-in, nonlinearity, and sensitivity to electronic noise and disturbances. To address these challenges, an STSMC is developed to overcome the nonlinearity and instability, while an extended state observer (ESO) estimates the ESA's displacement. Implemented on a real ESA model in MATLAB/Simulink, the ESO-based STSMC increases the ESA's travel range to 99.9% of its full gap despite noise, disturbance, and parametric uncertainty. The system's stability is proved using a Lyapunov approach.

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Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10906032
Primary Topic
Iterative Learning Control Systems
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article
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article

An Extended State Observer Based Super-Twisting Sliding Mode Controller for Electrostatic Actuators

Gianfranco Trovato, Anusree Mandali, Lili Dong
Iterative Learning Control Systems
article

An Extended State Observer Based Super-Twisting Sliding Mode Controller for Electrostatic Actuators

Gianfranco Trovato, Anusree Mandali, Lili Dong
article en

Abstract

This paper presents a super twisting sliding mode control (STSMC) system to stabilize a parallel-plate electrostatic actuator (ESA) and extend its operating range beyond the pull-in point. A voltage-controlled ESA is stable only within one-third of the full gap due to susceptibility to pull-in, nonlinearity, and sensitivity to electronic noise and disturbances. To address these challenges, an STSMC is developed to overcome the nonlinearity and instability, while an extended state observer (ESO) estimates the ESA's displacement. Implemented on a real ESA model in MATLAB/Simulink, the ESO-based STSMC increases the ESA's travel range to 99.9% of its full gap despite noise, disturbance, and parametric uncertainty. The system's stability is proved using a Lyapunov approach.

Cleveland State University (US), Lafayette College (US)
Affordable and clean energy
Openalex Percentile: Top 65%
Iterative Learning Control Systems
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