Autor: |
Baijun Lei, Haozhong Huang, Guixin Chen, Jianguo Liang, Huigui Long |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
|
Zdroj: |
Aerospace, Vol 11, Iss 5, p 344 (2024) |
Druh dokumentu: |
article |
ISSN: |
2226-4310 |
DOI: |
10.3390/aerospace11050344 |
Popis: |
Thrust constitutes a pivotal performance parameter for aircraft engines. Thrust, being an indispensable parameter in control systems, has garnered significant attention, prompting numerous scholars to propose various methods and algorithms for its estimation. However, research methods for estimating the thrust of the micro-turbojet engines used in unmanned aerial vehicles are relatively scarce. Therefore, this paper proposes a thrust estimator for micro-turbojet engines based on DBO (dung beetle optimization) utilizing bidirectional long short-term memory (BiLSTM) and a convolutional neural network (CNN). Furthermore, the efficacy of the proposed model is further validated through comparative analysis with others in this paper. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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