Paper Info
Title
Aircraft Control Parameter Estimation Using Self-Adaptive Teaching-Learning-Based Optimization with an Acceptance Probability.
Abstract
This work presents a metaheuristic (MH) termed, self-adaptive teaching-learning-based optimization, with an acceptance probability for aircraft parameter estimation. An inverse optimization problem is presented for aircraft longitudinal parameter estimation. The problem is posed to find longitudinal aerodynamic parameters by minimising errors between real flight data and those calculated from the dynamic equations. The HANSA-3 aircraft is used for numerical validation. Several established MHs along with the proposed algorithm are used to solve the proposed optimization problem, while their search performance is investigated compared to a conventional output error method (OEM). The results show that the proposed algorithm is the best performer in terms of search convergence and consistency. This work is said to be the baseline for purely applying MHs for aircraft parameter estimation.
Year
DOI
Venue
2021
10.1155/2021/4740995
Computational Intelligence and Neuroscience
DocType
Volume
ISSN
Journal
2021
1687-5265
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Yodsadej Kanokmedhakul100.34
Natee Panagant200.34
Sujin Bureerat300.34
Nantiwat Pholdee4398.08
Ali R Yildiz500.34