Identification of Asynchronous Machine Parameters by Evolutionary Techniques

Abstract

Four evolutionary techniques (scatter search, evolutionary programming, ant colony, and particle swarm algorithms) were used for off-line identification of three phase asynchronous machine parameters. Optimization techniques were then tested on two distinct machines. In order to evaluate how much good the achieved machines parameters obtained, experimental and simulation input-output behaviors are presented for each method. The performances in term of objective function and convergence time prove the effectiveness of this class of optimization methods.