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Adaptive physics-informed system modeling with control for nonlinear structural system estimation
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DOI：10.1016/j.cma.2025.118330.png)
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Abstract
En 中文
• Adaptive physics-informed modeling with control (APSMC): A novel digital twin framework integrating real-time adaptive filtering with proximal gradient updates to enable online identification of time-varying state-space parameters under arbitrary excitation. • Convergence to physically consistent optimal estimation: Theoretically proven within the stochastic subspace framework, APSMC integrates Kalman filter-based estimation with embedded physical constraints, ensuring convergence to a physically consistent optimal solution. • Robust validation through simulation and experiment: APSMC is validated via Duffing oscillator simulations, seismic analysis of frame structures, and scaled bridge experiments, demonstrating low computational cost and strong generalization.
Keywords:
adaptive physics-informed modeling
digital twin framework
proximal gradient updates
stochastic subspace identification
physically consistent estimation
Journal
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7.3
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