RF MEMS Switch Electrostatic Actuated Beam Stabilization Analysis Using Neural Network.

This paper presents a theoretical model to predict the electrical and mechanical behavior of Radio Frequency (RF) Microelectro Mechanical System (MEMS) switch. Using the basic force deflection calculation of the fixed-fixed beam, a stand-alone model for calculating the spring constant, critical stress and pull down voltage in static analysis of RF MEMS switch to understand the mechanical operation is obtained. An efficient neural network to analyze the position stabilization of electrostatically actuated beam with force distributed evenly across the section of beam used in MEMS switches has been proposed. The results from the neural model trained by Levenberg-Marquardt back propagation algorithm corresponds closely with those available in literature. [ABSTRACT FROM AUTHOR]