Implementation and comparative analysis of the optimisations produced by evolutionary algorithms for the parameter extraction of PSP MOSFET model |
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| Authors: | Sarman K Hadia RA Thakker Kirit R Bhatt |
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| Affiliation: | 1. V T Patel Department of Electronics and Communication, Charotar University of Science and Technology, Changa, Gujarat, India;2. Electronics and Communication Department, Viswakarma Government Engineering College, Chandkheda, Gujarat, India;3. Electronics and Communication Department, Sardar Vallabhbhai Patel Institute of Technology, Vasad, Gujarat, India |
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| Abstract: | The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (ABC), variant ABC and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that ABC algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic ABC algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant ABC and basic ABC algorithm for the parameter extraction of the MOSFET model; also the implementation of the ABC algorithm is shown to be simpler than that of the PSO algorithm. |
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| Keywords: | Evolutionary algorithm PSP model parameter extraction extraction strategy ABC algorithm ABC variant algorithm particle swarm optimisation |
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