Estimation of induction motor parameters using shuffled frog-leaping algorithm


Abstract:

This paper introduces a shuffled frog-leaping algorithm based method to approximate the equivalent circuit parameters of induction machines from the manufacturer data, such as nameplate data and motor performance characteristics. The steady-state equivalent circuit is applied for the simulations. The circuit parameters are found as the result for the error minimization function between the estimated and maker data. The suggested algorithm solves the parameter estimation problem and surpasses the solutions reached by differential evolution, particle swarm optimization and genetic algorithms. Therefore, this algorithm can be employed in motor energy management system for bettering the overall energy savings in industry. © 2012 Springer-Verlag Berlin Heidelberg.

Año de publicación:

2013

Keywords:

  • Genetic Algorithms
  • Induction Motor
  • Parameters estimation
  • Differential Evolution
  • Particle Swarm Optimization
  • Shuffled Frog-Leaping Algorithm

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Algoritmo

Áreas temáticas:

  • Física aplicada