Model guided extremum seeking control of electromagnetic micromirrors

Area of Science:

• * Robotics and Control Systems
• * Micro-electromechanical Systems (MEMS)

Background:

• * Electromagnetic micro-mirrors are crucial components in various optical systems.
• * Precise control is essential for effective target tracking applications.
• * Existing control methods may lack adaptability and optimal step-size selection.

Purpose of the Study:

• * To develop a simplified dynamic model for electromagnetic micro-mirrors.
• * To design a model-guided extremum seeking control (MGESC) scheme.
• * To improve the performance and robustness of micro-mirror control systems for target tracking.

Main Methods:

• * Construction of a simplified dynamic model for electromagnetic micro-mirror characteristics.
• * Development of a model-guided extremum seeking control (MGESC) algorithm.
• * Integration of backtracking line search for automatic step-size estimation in each iteration.
• * Mathematical proof of the convergence for the proposed MGES algorithm.

Main Results:

• * The simplified dynamic model effectively captures key electromagnetic micro-mirror behaviors.
• * The MGESC scheme with backtracking line search demonstrated improved target tracking performance.
• * Automatic step-size estimation led to enhanced control system efficiency.
• * Convergence of the MGES algorithm was theoretically established.

Conclusions:

• * The proposed MGESC scheme offers an effective approach for controlling electromagnetic micro-mirrors.
• * The method enhances target tracking accuracy and system performance.
• * The developed control strategy is validated through simulations and experimental results.