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)

Abstract

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
Volume17
Issue number4
DOIs
Publication statusPublished - 2012

Fingerprint

Drilling
Identification (control systems)
Prototype
Nonlinear Process
Black Box
Nonlinear Systems
Nonlinear systems
Residual Analysis
Analytical Modeling
Selection Procedures
Drilling rigs
Modeling Method
Least Square Method
Model Selection
Model
Pole
Nonlinearity
Mathematical Model
Poles
Output

Keywords

  • 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

Cite this

Identification of a Box-Jenkins model for rotary drilling laboratory prototype. / Abdul Majeed, Fesmi; Karki, Hamad; Karkoub, Mansour; Abdel Magid, Youssef.

In: International Journal of Modelling, Identification and Control, Vol. 17, No. 4, 2012, p. 302-314.

Research output: Contribution to journalArticle

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