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Parameter identification of nonlinear system using an improved Lozi map based chaotic optimization algorithm (ILCOA)

  • S. Mohammadreza Ebrahimi
  • Milad MalekzadehEmail author
  • Mojtaba Alizadeh
  • S. Hassan HosseinNia
Original Paper
  • 19 Downloads

Abstract

In this paper, an efficient stochastic optimization algorithm is presented for parameter identification of nonlinear systems. Due to its robust performance, short running time and desirable potency to find local minimums the Lozi map-based chaotic optimization algorithm is an appropriate choice to estimate unknown parameters of nonlinear dynamic systems. To enhance the identification efficacy and in order to escape local minimum, a modified version of this algorithm with higher stability and better performance is rendered in this paper. An Improved Lozi map-based chaotic optimization algorithm (ILCOA) is employed to identify three nonlinear systems and the performance of the proposed algorithm is compared with other optimization algorithms. The simulation results of identification endorse the effectiveness of the proposed method.

Keywords

Identification Stochastic optimization ILCOA Nonlinear systems 

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • S. Mohammadreza Ebrahimi
    • 1
  • Milad Malekzadeh
    • 1
    Email author
  • Mojtaba Alizadeh
    • 2
  • S. Hassan HosseinNia
    • 3
  1. 1.Faculty of Electrical EngineeringBabol Noshirvani University of TechnologyBabolIran
  2. 2.Faculty of Electrical EngineeringK.N. Toosi University of TechnologyTehranIran
  3. 3.Department of Precision and Microsystems EngineeringDelft University of TechnologyDelftThe Netherlands

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