Iterative Learning Control for Quasi-Static MEMS Mirror with Switching Operation
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
This paper reports an iterative learning control (ILC) to compensate for the errors by the switching operation and the modeling inaccuracies for a quasi-static (QS) MEMS mirror. The modeling errors and uncertainties in dynamics with the switching operation between electrodes result in undesirable oscillations in beam positioning. A wideband frequency-domain ILC is proposed for a QS MEMS mirror with a flatness-based feedforward control. The improvement of the residual oscillations is demonstrated by reduced root mean square (RMS) errors for a 2 Hz and a 2-degree-amplitude sawtooth reference with a factor 69.9.
Details
| Original language | English |
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| Title of host publication | 2023 IEEE 36th International Conference on Micro Electro Mechanical Systems (MEMS) |
| Place of Publication | München |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 538-541 |
| Number of pages | 4 |
| ISBN (electronic) | 978-1-6654-9308-6 |
| ISBN (print) | 978-1-6654-9309-3 |
| Publication status | Published - 2023 |
| Peer-reviewed | Yes |
Publication series
| Series | IEEE International Conference on Micro Electro Mechanical Systems (MEMS) |
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| Volume | 2023-January |
| ISSN | 1084-6999 |
Conference
| Title | 36th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2023 |
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| Duration | 15 - 19 January 2023 |
| City | Munich |
| Country | Germany |
External IDs
| ORCID | /0000-0003-3259-4571/work/142249669 |
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Keywords
ASJC Scopus subject areas
Keywords
- Electrostatic Actuation, Iterative Learning Control, Quasi-Static MEMS Mirror, Switching Operation