pull-in phenomenon in the electrostatically micro-switch ‎suspended between two conductive plates using the artificial ‎neural network

Artificial neural networks (ann) are designed to evaluate the pull-in voltage of mems switches. the mathematical model of a micro-switch subjected to electrostatic force is preliminarily illustrated to get the relevant equations providing static deflection and pull-in voltage. adopting the step-by-step linearization method together with a galerkin-based reduced order model, numerical results in terms of pull-in voltage are obtained to be employed in the training process of ann. then, feed forward back propagation anns are designed and a learning process based on the levenberg-marquardt method is performed. the ability of designed neural networks to determine pull-in voltage have been compared with previous results presented in experimental and theoretical studies and it has been shown that the presented method has a good ability to approximate the threshold voltage of micro switch. furthermore, the geometric and physical effect of the micro-switch on the pull-in voltage was also examined using these designed networks and relevant findings were provided.