Variational-based data-driven model identification of micro resonator systems

Abstract Accurate identification of the dynamic system equations governing micro-electro-mechanical system (MEMS) resonators is critical for optimising their design and performance. This paper proposes a data-driven method based on the variational principle for dynamic system identification of MEMS resonators. Compared with traditional parametric modelling methods, this method does not rely on predefined models, but directly processes and analyses experimental data, which has higher flexibility and accuracy in identifying complex micro-scale systems. The research demonstrates the application of this method to two types of MEMS devices with distinct nonlinear characteristics. The results show that the method is not only suitable for theoretical research but also effective in identifying dynamic systems in practical applications. Furthermore, the system response under different excitation is predicted, which proves that it has good generalisation capabilities. This opens new avenues for dynamic analysis of MEMS resonators.