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This paper proposes a fuzzy adaptive control method integrating an extended state observer (ESO) with a multi-segment nonlinear state error feedback (NLSEF) function. The proposed approach introduces two key innovations: (1) a fuzzy logic-based ESO bandwidth adaptation mechanism that enhances disturbance estimation accuracy across varying wind conditions and (2) a multi-segment NLSEF controller that replaces the conventional two-segment design, refining the system\u2019s response to different disturbances. Flight experiments conducted under no-wind, headwind, and crosswind conditions demonstrate that the proposed method reduces position error by 9.6%\u201361.5% compared to traditional approaches.<\/jats:p>","DOI":"10.1177\/01423312251327297","type":"journal-article","created":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T00:29:07Z","timestamp":1745540947000},"page":"1827-1839","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["ESO-based fuzzy adaptive control of tiltrotor UAV against wind disturbance"],"prefix":"10.1177","volume":"48","author":[{"given":"Xiaomei","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingxun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, China"},{"name":"Institute of Unmanned System, Beihang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9873-156X","authenticated-orcid":false,"given":"Jiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ningjun","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Unmanned System, Beihang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7901-261X","authenticated-orcid":false,"given":"Zhihao","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, China"},{"name":"Institute of Unmanned System, Beihang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,4,24]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2021.109790"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.2514\/6.2021-3215"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3080276"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICUAS.2017.7991379"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.buildenv.2017.12.016"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2020.106238"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2021.107035"},{"key":"e_1_3_2_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2022.107818"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2008.2011621"},{"key":"e_1_3_2_11_1","doi-asserted-by":"publisher","DOI":"10.3390\/s20247084"},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2930489"},{"key":"e_1_3_2_13_1","volume-title":"Disturbance Observer-Based Control: Methods and Applications","author":"Li S","year":"2014","unstructured":"Li S, Yang J, Chen WH, et al. (2014) Disturbance Observer-Based Control: Methods and Applications. Boca Raton, FL: CRC press."},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.23919\/ChiCC.2019.8865272"},{"key":"e_1_3_2_15_1","unstructured":"Liu N (2019) Study on efficient flight mode transition control of V\/STOL UAV. PhD Thesis Beihang University Beijing China."},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/math12132077"},{"key":"e_1_3_2_17_1","unstructured":"Lu D (2023) Study of a particle deposition prediction model based on fan flow field. PhD Thesis Harbin Institute of Technology Harbin China."},{"issue":"66","key":"e_1_3_2_18_1","doi-asserted-by":"crossref","DOI":"10.1126\/scirobotics.abm6597","article-title":"Neural-fly enables rapid learning for agile flight in strong winds","volume":"7","author":"O\u2019Connell M","year":"2022","unstructured":"O\u2019Connell M, Shi G, Shi X, et al. (2022) Neural-fly enables rapid learning for agile flight in strong winds. 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