Model guided extremum seeking control of electromagnetic micromirrors

Sun, Wanyan; Tan, Yonghong

doi:10.1038/s41598-021-97098-6

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…There are different types of micromirror movement diversity. A general classification is made as electrostatic [12], [13], Electrothermal [14], [15], electromagnetic [16], [17], and Piezoelectric [18]. In this classification, the drive-actuator element and the material used are of great importance.…”

Section: Introductionmentioning

confidence: 99%

Computational model for the nonlinear dynamic response of MEMS-based micromirror

Ertugrul¹,

Ersoy²,

Ragulskis³

2022

Vib. proced.

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In this study, it is aimed to perform Finite Element Analysis (FEA) of micromirror based on Micro-Electro-Mechanical Systems (MEMS) and to examine the nonlinear and dynamic responses of this system. Micromirror devices are indispensable, especially for optical systems and form the basis of them. In this work, dynamic and nonlinear responses of micromirror with 4 symmetric arms and one reflective surface were investigated. During the design and modeling, it is assumed that the upper and lower layers of the reflective surface have equal tensile and compressive stresses. The analysis of the system was obtained by applying a force of up to 30 GPa Prestressed on the reflective surface. The design and FEA of the micromirror system were made with the Comsol Multiphysics program. The nonlinear response of the analysis was carried out with the MATLAB program. This model, which has the most basic design of micromirror structures used in optical systems, is thought to be a source for a good examination of the nonlinear dynamic model and for understanding more complex structures.

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Section: Introductionmentioning

confidence: 99%

Computational model for the nonlinear dynamic response of MEMS-based micromirror

Ertugrul¹,

Ersoy²,

Ragulskis³

2022

Vib. proced.

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Robust data‐driven dynamic optimization using a set‐based gradient estimator

Kashani,

Panahi,

Chakrabarty

et al. 2024

Optim Control Appl Methods

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This article presents an extremum‐seeking control (ESC) algorithm for unmodeled nonlinear systems with known steady‐state gain and generally non‐convex cost functions with bounded curvature. The main contribution of this article is a novel gradient estimator, which uses a polyhedral set that characterizes all gradient estimates consistent with the collected data. The gradient estimator is posed as a quadratic program, which selects the gradient estimate that provides the best worst‐case convergence of the closed‐loop Lyapunov function. We show that the polyhedral‐based gradient estimator ensures the stability of the closed‐loop system formed by the plant and optimization algorithm. Furthermore, the estimated gradient provably produces the optimal robust convergence. We demonstrate our ESC controller through three benchmark examples and one practical example, which shows our ESC has fast and robust convergence to the optimal equilibrium.

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