Capacitive Charge-based Self-Sensing for Resonant Electrostatic MEMS mirrors
| Autor: | David Brunner, Richard Schroedter, Georg Schitter, Han Woong Yoo |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Microelectromechanical systems
Physics 0209 industrial biotechnology Displacement current business.industry Capacitive sensing 020208 electrical & electronic engineering High voltage 02 engineering and technology Signal Vibration Op amp integrator 020901 industrial engineering & automation Optics Control and Systems Engineering Comb drive 0202 electrical engineering electronic engineering information engineering business |
| Zdroj: | IFAC-PapersOnLine. 53:8553-8558 |
| ISSN: | 2405-8963 |
| Popis: | This paper proposes capacitive charge-based self-sensing by integration of the comb drive intrinsic displacement current for resonant electrostatic MEMS mirrors in order to solve the problem of robust feedback for laser scanning in mobile light detection and ranging (Lidar) application. A two-channel switched current integrator circuit is implemented to determine the deflection angle and to distinguish the rotation direction from the asymmetric comb drive charge. Parameters of the MEMS mirror are calibrated with the deflection angle by an optical PSD setup. The resonant electrostatic MEMS mirror is parametrically driven by a square wave high voltage signal, which means, that the charge measurement is only available during the time with non-zero drive signal. From the partly available charge measurements, a nonlinear observer is developed to estimate the mirror state at all time for a potential feedback control. The feasibility for online position estimation is proven by simulation using experimental charge and deflection angle measurements resulting in less than 2% error at full amplitude operation. Finally, the performance of the proposed method is discussed for realization of active MEMS mirror feedback control, overcoming imprecise motions due to structural nonlinearities as well as external disturbances like vibration and climate variation. |
| Databáze: | OpenAIRE |
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