Identification of Dynamic Models by Using Metaheuristic Algorithms

Authors

  • Mustafa Danaci Erciyes University
  • Fehim Koylu Erciyes University
  • Zaid Ali Al-Sumaidaee Erciyes University

DOI:

https://doi.org/10.34306/ajri.v3i1.492

Keywords:

Dynamic Weighing System(DWS),System Identification(SI),Parameters Predicted, Genetic Algorithm (GA), Biogeography-Based Optimization Algorithm (BBO), Ant Colony Optimization Algorithm (ACO), Artificial Bee Colony Algorithm (ABC).

Abstract

A modified versions of metaheuristic algorithms are presented to compare their performance in identifying the structural dynamic systems. Genetic algorithm, biogeography based optimization algorithm, ant colony optimization algorithm and artificial bee colony algorithm are heuristic algorithms that have robustness and ease of implementation with simple structure. Different algorithms were selected some from evolution algorithms and other from swarm algorithms   to boost the equilibrium of global searches and local searches, to compare the performance and investigate the applicability of proposed algorithms to system identification; three cases are suggested under different conditions concerning data availability, different noise rate and previous familiarity of parameters. Simulation results show these proposed algorithms produce excellent parameter estimation, even with little measurements and a high noise rate.

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Published

2021-08-23

How to Cite

Danaci, M., Koylu, F., & Al-Sumaidaee, Z. A. (2021). Identification of Dynamic Models by Using Metaheuristic Algorithms. ADI Journal on Recent Innovation, 3(1), 36–58. https://doi.org/10.34306/ajri.v3i1.492

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