Subjects
-Tags
-Abstract
This research presents an investigation into the development of system identification using intelligent algorithms. A simulation platform of a flexible beam vibration using finite difference (FD) method is used to demonstrate the capabilities of the identification algorithms. A number of approaches and algorithms for system identifications are explored and evaluated. These identification approaches using (a) traditional Recursive Least Square (RLS) filter, (b) Genetic Algorithms (GAs) (c) Adaptive Neuro_Fuzzy Inference System (ANFIS) model (d) General Regression Neural Network (GRNN) and (e)Bees Algorithm (BA). The above algorithms are used to estimate a linear discrete second order model for the flexible beam vibration. The model is implemented, tested and validated to evaluate and demonstrate the merits of the algorithms for system identification. Finally, a comparative performance of error convergence of the algorithms is presented and discussed.
DOI
10.21608/asat.2009.23751
Keywords
system identification, adaptive control, intelligent identification, recursive least squares algorithm, Genetic Algorithm, ANFIS, Bees Algorithm
Authors
Affiliation
Department of Computer Science, University of Helwan, Helwan, Egypt, Faculty of
Engineering, Helwan University.
Email
-City
-Orcid
-Affiliation
-Email
-City
-Orcid
-Affiliation
-Email
-City
-Orcid
-Affiliation
-Email
-City
-Orcid
-Article Issue
AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT- 13, May 26 – 28, 2009
Link
https://asat.journals.ekb.eg/article_23751.html
Detail API
https://asat.journals.ekb.eg/service?article_code=23751
Publication Title
International Conference on Aerospace Sciences and Aviation Technology
Publication Link
https://asat.journals.ekb.eg/
MainTitle
System Identification Using Intelligent Algorithms