Identification of Stochastic Process in MATLAB

Authors

  • Ojonugwa Adukwu Federal University of Technology Akure

DOI:

https://doi.org/10.24203/ajet.v7i3.5813

Keywords:

System Identification, model structures, process noise

Abstract

The system identification toolbox in MATLAB has been successfully used to compare model identification of a first order system subjected to high and low disturbances. The model structures used are FIR, ARX, AMX, OE and BJ. The obtained Model was validated using data generated from the actual process. It shows that the more the variance of the noise input into the system, the more difficult it is for the model identified to reproduce that validation data obtained from process response. Also when the measurement noise has zero mean and low variance, the effect on the steady state gain and other process parameters is negligible.

References

Kollar I., Pintelon R., Schoulkens J. (1991), Frequency Domain Identification ToolBox for MATLAB, IFAC Proceedings, 24(3), pp 1243-1247.

Jimenez M.J., Madsen H., Anderson K.K., (2008), Identification of the Main Characteristics of Building Components Using MATLAB, Journal of Building and Environment, 43(2), pp. 170-180.

Yuen K.V., Mu H.Q. (2015)., Real-Time Identification: An Algorithm for Simultaneous Model Class Selection and Parametric Identification, Journal of Computer-Aided Civil and Infrastructure Engineering, pp 1-17.

Adukwu O., Oku D. E. (2018), Modeling Analysis and Monitoring DC Motor Using Proportional-Integral Controller and Kalman Filter, International Journal of Science and Research, 7(8), pp 454-458.

Ljung L. (1987), System Identification: Theory for User, Prentice-Hall, Englewood Cliffs, NJ, USA.

Ljung L. (1998), System Identification, Birkhäuser, Boston, MA, USA.

Downloads

Published

2019-06-16

How to Cite

Adukwu, O. (2019). Identification of Stochastic Process in MATLAB. Asian Journal of Engineering and Technology, 7(3). https://doi.org/10.24203/ajet.v7i3.5813

Issue

Vol. 7 No. 3 (2019): June 2019

Section

Articles

License

  • Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
  • It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
  • The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
  • The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
  • The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.