Vol 6 No 1. (2019)
Articles

System Identification and Model Validation of Recursive Least Squares Algorithm for Box–Jenkins Systems

Published December 23, 2019
Nasar Aldian Ambark Shashoa
Electrical and Electronics Engineering Department, Azzaytuna University
Abdurrezag S. Elmezughi
Computer Engineering Department, Azzaytuna University
Ibrahim N. Jleta
Department of Electrical Engineering, Libyan Academy of Graduate Studies
Nasser B. Ekreem
Computer Engineering Department, Azzaytuna University
View:
Pdf
How to Cite

APA

Aldian Ambark Shashoa, N., S. Elmezughi, A., N. Jleta, I., & B. Ekreem, N. (2019). System Identification and Model Validation of Recursive Least Squares Algorithm for Box–Jenkins Systems. Recent Innovations in Mechatronics, 6(1.), 1-6. https://doi.org/10.17667/riim.2019.1/4.

Abstract

In this paper, a new-type recursive least squares algorithm is proposed for identifying the system model parameters and the noise model parameters of Box–Jenkins Systems. The basic idea is based on replacing the unmeasurable variables in the information vectors with their estimates. The proposed algorithm has high computational efficiency because the dimensions of the involved covariance matrices in each subsystem become small. Validation of the model is evaluated using some statistical methods, Which, best-fit criterion and Histogram. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.