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 language | British English |
|---|---|
| Pages (from-to) | 302-314 |
| Number of pages | 13 |
| Journal | International Journal of Modelling, Identification and Control |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2012 |
Keywords
- Box-Jenkins model
- Drill string
- Least squares
- Modelling
- Non-linear process
- System identification