Research on Co-Optimization of Control Logic and Structural Design for Intelligent MEMS via Digital Twin Technology

Yuanxu Zhou

Simen Owen Academic Proceedings Series, 2026, vol. 3, 101-113

Abstract: The performance of Micro-Electro-Mechanical Systems (MEMS) depends on the coordinated interaction between structural design and control logic. However, existing design methodologies treat these domains independently, lacking real-time feedback and multi-objective optimization. To address this limitation, this study proposes a digital-twin-driven co-optimization framework that integrates structural and control parameter tuning within a unified, synchronized environment. The framework combines finite-element modeling, real-time sensor feedback, and a hybrid evolutionary-gradient optimization algorithm to jointly minimize energy consumption, response delay, and resonance deviation under physical constraints. Experimental validation on a silicon-based micro-cantilever MEMS demonstrates a precision improvement of 4.6%, energy reduction of 18.7%, and response delay decrease of 23.5% compared to baseline methods. The framework achieved stable convergence within 150 epochs, with a 46% lower variance and performance retention above 95% across piezoelectric and thermal MEMS devices. SHAP-based interpretability analysis further revealed that stiffness, damping, and control gain jointly explain 63% of performance variance, confirming the physical consistency of the model. These results indicate that integrating digital twin synchronization with hybrid optimization provides a reproducible and interpretable pathway for intelligent MEMS co-design, enhancing precision, efficiency, and robustness across multi-physics operating conditions.

Keywords: digital twin; MEMS co-optimization; hybrid evolutionary-gradient algorithm; multi-physics robustness; structural-control coupling (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:axf:soapsa:v:3:y:2026:i::p:101-113

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