Title :
Parameter identification of induction motor based on particle swarm optimization
Author :
Picardi, C. ; Rogano, N.
Author_Institution :
Calabria Univ., Rende
Abstract :
The paper deals with the application of the particle swarm optimization (PSO) to the parameter identification of the induction motor. A suitable model of the motor with a specific parameter vector, including electromagnetic and mechanical parameters, is given. The simulation results, presented in the paper, mainly have the purpose to compare the PSO, the genetic algorithm (GA) and a modified PSO with a function "stretching" (SPSO) in terms of the behaviours of the best fitness and the average fitness versus the number of evaluations and of the reconstruction of the output variables by means of the identified parameters
Keywords :
genetic algorithms; induction motors; parameter estimation; particle swarm optimisation; GA; electromagnetic parameters; genetic algorithm; induction motor; mechanical parameters; parameter identification; particle swarm optimization; Electromagnetic induction; Electromagnetic modeling; Evolutionary computation; Genetic algorithms; Induction motors; Parameter estimation; Particle swarm optimization; Stochastic processes; Time factors; Time measurement;
Conference_Titel :
Power Electronics, Electrical Drives, Automation and Motion, 2006. SPEEDAM 2006. International Symposium on
Conference_Location :
Taormina
Print_ISBN :
1-4244-0193-3
DOI :
10.1109/SPEEDAM.2006.1649908