In this paper, data filtering based Recursive Least Squares algorithm of linear Box–Jenkins systems is proposed for fault detection. The system is decomposed into two subsystems, one containing the parameters of the system model and the other containing the parameters of the noise model, and these parameters of the system model and the noise model are estimated. The model validation is tested using two statistical methods, histogram and mean square errors. The residual is generated based on the proposed algorithm to design the threshold and therefore, this design is used for fault detection. Simulation results are performed to illustrate the algorithm performance.
1st Mosharaka International Conference on Control and Systems Engineering (MIC-Control 2021)
Congress
2021 Global Congress on Electrical Engineering (GC-ElecEng 2021), 10-12 December 2021, Valencia, Spain
Pages
--1
Topics
Intelligent Control Systems Digital Control Systems
ISSN
2227-331X
DOI
BibTeX
@inproceedings{1193ElecEng2021,
title={Fault Detection Based on Validated Model of Data Filtering Based RLS Algorithm For Box-Jenkins Systems},
author={Nasar Aldian Shashoa, and Ahmed Abougarair},
booktitle={2021 Global Congress on Electrical Engineering (GC-ElecEng 2021)},
year={2021},
pages={--1},
doi={}},
organization={Mosharaka for Research and Studies}
}
