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Online Optimization Method for Nonlinear Model-Predictive Control in Angular Tracking for MEMS Micromirror.

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Summary

This study introduces a precise angular tracking control strategy using nonlinear predictive optimization control (POC) for electromagnetic driven deflection micromirror (EDDM) systems. The method effectively handles model uncertainty and noise for improved performance.

Keywords:
Hammerstein architectureangular trackinghysteresismicromirrorpredictive control

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Area of Science:

  • Control Systems Engineering
  • Mechatronics
  • Nonlinear Dynamics

Background:

  • Electromagnetic driven deflection micromirror (EDDM) systems exhibit complex nonlinear characteristics and are susceptible to model uncertainty and noise.
  • Precise angular tracking is crucial for the performance of EDDM systems in various applications.
  • Existing control strategies may struggle to adequately address the inherent nonlinearities and uncertainties in these systems.

Purpose of the Study:

  • To develop and validate a precise angular tracking control strategy for EDDM systems.
  • To address model uncertainty and noise interference using an online Hammerstein-model-based predictive optimization control (POC) approach.
  • To ensure the stability and effectiveness of the proposed control strategy through theoretical analysis and experimental validation.

Main Methods:

  • A nonlinear predictive optimization control (POC) strategy is designed based on an online Hammerstein model.
  • A rate-dependent Duhem model is employed to characterize the nonlinear sub-model, capturing multi-valued mapping.
  • The linear sub-model's predictive output is derived using a Diophantine function, with iterative control values determined by data-driven parameter estimation and a defined cost function.

Main Results:

  • The proposed online Hammerstein-model-based POC effectively manages model uncertainty and noise interference.
  • The control value is adaptively determined by real-time updates of the model residual and cost function.
  • Experimental results demonstrate the significant effectiveness of the developed control technique in achieving precise angular tracking.

Conclusions:

  • The developed nonlinear predictive optimization control (POC) strategy offers a robust solution for precise angular tracking in EDDM systems.
  • The integration of an online Hammerstein model and data-driven parameter estimation enhances control performance under uncertainty.
  • The validated control technique provides a reliable method for improving the operational precision of electromagnetic driven deflection micromirror systems.