Simulation and Analysis of Hybrid Gravitational Search Optimization Algorithm with Artificial Neural Network for Optimizing RF_MEMS Switch Parameters

Abstract

Now a day s MEMS (Micro Electromechanical System) switch used in the design newlineof antenna rearrangement and its optimization of switch parameters, it is an attractive and newlineimportunate problem in the research field. As this RF-MEMS technology frequently newlineamplifying and it is a process to create the integration of small devices, which is the newlineamalgamation of electrical and mechanical elements. The IC batch processing technique is newlineused for the fabrication and the size range is from few micrometers to millimeters. The newlineMEMS with microstructures, actuators, sensor and micro-electronics are combined to newlineplace over the similar silicon chip. The domain of the system changes like thermal, newlinemechanical, magnetic and electromagnetic factors are predicted by Microsensors. newlineTherefore, the signal and information are processed with a Microelectronics processor but newlinecertain environment changes will be created in the presence of Microactuators. The Micro newlinestructures are difficult to study directly due to their small size. The huge amount of newlineprocedures and structures are introduced to increase accuracy and efficiency measurement. newlineThe proposed work is inspired by excellent performance of RF-MEMS Switch over newlineother semiconductor devices like FET and PIN diode and its latent qualities is useful in newlinewireless, satellite and Mobile communication. The proposed technique s main intention newlineis to optimize the RF-MEMS Switch parameters using Hybrid gravitational search newlineOptimization (HGSO) algorithm with Artificial Neural Network (ANN), and for validation newlineof optimized RF-MEMS Switch it is tested with re-configurable antenna. Basically, the newlineproposed RF-MEMS Switch parameters have chosen here are, beam width, length, gaps, newlineand thickness of the switch. The combination of Artificial Neural Network with Gravitational Search Optimization algorithm has been implemented by using the MATLAB 2016a platform.