An artificial neural network supported performance degradation modeling for electro-hydrostatic actuator-Reference-Cited by-同舟云学术

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An artificial neural network supported performance degradation modeling for electro-hydrostatic actuator

Published:2022-05-18 Issue:6 Volume:44 Page:
ISSN:1678-5878
Container-title:Journal of the Brazilian Society of Mechanical Sciences and Engineering
language:en
Short-container-title:J Braz. Soc. Mech. Sci. Eng.

Author:

Nie Songlin,Gao Jianhang,Ma Zhonghai^ORCID,Yin Fanglong,Ji Hui

Funder

National Natural Science Foundation of China

Beijing Postdoctoral Research Foundation

General Program of Science and Technology Development Project of Beijing Municipal Education Commission

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,General Engineering,Aerospace Engineering,Automotive Engineering,Industrial and Manufacturing Engineering,Applied Mathematics

Link

https://link.springer.com/content/pdf/10.1007/s40430-022-03518-7.pdf

Reference36 articles.

1. Navatha A, Hiremath Somashekhar S, Singaperumal M, Karunanidhi S, Apratim T (2016) Review on electro hydrostatic actuator for flight control. Int J Fluid Power 17(2):125–145. https://doi.org/10.1080/14399776.2016.1169743

2. Kumar M (2021) A survey on electro hydrostatic actuator: architecture and way ahead. Mater Today Proc 45(7):6057–6063. https://doi.org/10.1016/j.matpr.2020.10.049

3. Lim GH, Chua PSK, He YB (2003) Modern water hydraulics—the new energy-transmission technology in fluid power. Appl Energy 76(1–3):239–246. https://doi.org/10.1016/S0306-2619(03)00064-3

4. Yang HY, Panm M (2015) Engineering research in fluid power: a review. J Zhejiang Univ Sci A (Appl Phys Eng) 16(6):427–442. https://doi.org/10.1631/jzus.A1500042

5. Kim HM, Park SH, Lee JM, Kim JS (2010) A robust control of electro hydrostatic actuator using the adaptive back-stepping scheme and fuzzy neural networks. Int J Precis Eng Manuf 11(2):227–236. https://doi.org/10.1007/s12541-010-0026-z

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