System identification based on heuristic approaches

Medhat Awadalla, Dawood Al-Abri, Ali Al-Lawati, Samir Al-Busaidi

Research output: Contribution to journalArticlepeer-review


This paper presents an investigation of the development of system identification using intelligent algorithms. A simulation platform of a flexible beam vibration using finite difference (FD) method is accomplished to demonstrate the capabilities of the identification algorithms. Three heuristic approaches for system identification are explored and evaluated. These identification approaches are, Adaptive Neuro Fuzzy Inference System (ANFIS) model, Bees Algorithm (BA) and Particle Swarm Optimization, PSO. The above approaches are used to estimate a linear discrete second order model for the flexible beam vibration. The model is implemented, tested and validated to demonstrate the merits of the algorithms for system identification. Finally, a qualitative comparison have been accomplished to address the system performance in terms of error convergence of the proposed approaches. The achieved results of intensive simulated experiments show that PSO outperforms the other approaches.

Original languageEnglish
Pages (from-to)715-731
Number of pages17
JournalInternational Journal of Control Theory and Applications
Issue number2
Publication statusPublished - 2015


  • Adaptive control
  • Bees algorithm
  • Intelligent identification
  • PSO
  • System identification

ASJC Scopus subject areas

  • General Computer Science


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