Follow-up study of aircraft parameter estimation for lateral dynamics using self-adaptive teaching-learning based optimization with acceptance probability
1
Issued Date
2025-04-03
Resource Type
ISSN
25396161
eISSN
25396218
Scopus ID
2-s2.0-105007459519
Journal Title
Engineering and Applied Science Research
Volume
52
Issue
3
Start Page
251
End Page
259
Rights Holder(s)
SCOPUS
Bibliographic Citation
Engineering and Applied Science Research Vol.52 No.3 (2025) , 251-259
Suggested Citation
Kanokmedhakul Y., Pholdee N. Follow-up study of aircraft parameter estimation for lateral dynamics using self-adaptive teaching-learning based optimization with acceptance probability. Engineering and Applied Science Research Vol.52 No.3 (2025) , 251-259. 259. doi:10.14456/easr.2025.22 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/110684
Title
Follow-up study of aircraft parameter estimation for lateral dynamics using self-adaptive teaching-learning based optimization with acceptance probability
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Abstract
This paper is a follow-up on using self-adaptive teaching-learning based optimization with an acceptance probability (SATLBO-AP), tailored specifically for aircraft parameter estimation, and extended to aircraft lateral dynamics, previously tested for aircraft longitudinal dynamics. The lateral dynamic is more complicated than the longitudinal with additional parameters, input and output. Since the problem has changed, the performance of SATLABO-AP requires reevaluation. Thus, a comparison between newly developed algorithms and recently proposed algorithms is conducted. The problem setup is carried out in a way similar to earlier work, but with a lateral dynamic. The results show that SATLBO-AP outperforms other algorithms in terms of convergence and consistency regarding noise level added to the validation signal.