Identification of a Box-Jenkins model for rotary drilling laboratory prototype

Fesmi Abdul Majeed, Hamad Karki, Mansour Karkoub, Youssef Abdel Magid

Research output: Contribution to journalArticle

3 Citations (Scopus)


Conventionally, analytical modelling is used to analyse the dynamics of complex non-linear processes. This paper presents identification of mathematical models by the black box modelling method for non-linear systems. The non-linear system concerned in this work is a laboratory prototype of a rotary drilling rig. The system concerned is distinguished for its additive non-linearity at the output end. The step by step analysis of the procedures and criteria used to select an accurate model for a non-linear process by the black box identification method is explained. The model identified in the paper is a Box-Jenkins model. The model selection procedure uses least squares method, pole zero plots and residual analysis. Accurate simulation results with less than 0.05% error are obtained. The identified Box-Jenkins model is validated by a twofold validation procedure.

Original languageEnglish
Pages (from-to)302-314
Number of pages13
JournalInternational Journal of Modelling, Identification and Control
Issue number4
Publication statusPublished - 2012



  • Box-Jenkins model
  • Drill string
  • Least squares
  • Modelling
  • Non-linear process
  • System identification

ASJC Scopus subject areas

  • Computer Science Applications
  • Applied Mathematics
  • Modelling and Simulation

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