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. 2021 Dec 20:2021:4740995.
doi: 10.1155/2021/4740995. eCollection 2021.

Aircraft Control Parameter Estimation Using Self-Adaptive Teaching-Learning-Based Optimization with an Acceptance Probability

Yodsadej Kanokmedhakul  1 , Natee Panagant  1 , Sujin Bureerat  1 , Nantiwat Pholdee  1 , Ali R Yildiz  2
Affiliations

Aircraft Control Parameter Estimation Using Self-Adaptive Teaching-Learning-Based Optimization with an Acceptance Probability

Yodsadej Kanokmedhakul et al. Comput Intell Neurosci. .

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.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
Aircraft coordinate systems.
Figure 2
Figure 2
The state time response used as real flight data.
Figure 3
Figure 3
Acceptance probability scheduling.
Figure 4
Figure 4
Average fitness RMSE values of 20 individual runs without noise from the top 4 algorithms.
Figure 5
Figure 5
Comparison between simulated data with noise 5% and without noise from SaTLBO-AP best result.
Figure 6
Figure 6
Comparison between simulated data with noise 10% and without noise from SaTLBO-AP best result.
Algorithm 1
Algorithm 1
TLBO.
Algorithm 2
Algorithm 2
Algorithm 2 SaTLBO-AP.
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