MESFET DC model parameter extraction using adaptive accelerated exploration particle swarm optimizer

Abstract

This paper presents an application of Adaptive Accelerated Exploration Particle Swarm Optimization (AAEPSO) algorithm for extracting DC model parameters of a fabricated GaAs based Metal Extended Semiconductor Field Effect Transistor (MESFET). The AAEPSO algorithm is a variant of Particle swarm optimization algorithm that has proven to outperfrom basic PSO in solving benchmark problems. In this work we applied this algorithm to extract the MESFET model parameters by minimizing the error between the measured and modeled drain current. The performance of this approach is compared with popular algorithms like Simulated Annealing, Complex Method (CM), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) algorithms based on the (i) mean square error between the measured and modeled drain current, and (ii) convergence time. The comprehensive analysis of AAEPSO is carried out on four different MESFET DC models. Simulation results indicate that the AAEPSO algorithm gives good qaulity of solution in all the cases where as complex method takes less time for executing each iteration. © 2012 Springer-Verlag.