{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T14:47:09Z","timestamp":1764859629994,"version":"3.43.0"},"reference-count":26,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Hubei Provincial Natural Science Foundation for Innovation Groups, China","award":["2021CFA026"],"award-info":[{"award-number":["2021CFA026"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52071153"],"award-info":[{"award-number":["52071153"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:p>Due to the nonlinearity, strong coupling, and uncertain parameters of autonomous underwater vehicle (AUV), it is difficult to build an accurate dynamic model, which makes precise control of AUV extremely challenging. To handle the precise heading-following problem of AUV, this paper proposes an iterative learning-based redefine model-free adaptive heading control (IL-RMFAC) method for the underactuated AUV with unknown disturbances based on data driven. The control scheme consists of a learning control algorithm, a parameter iterative update algorithm, and a parameter reset algorithm. It is designed using only the input and output (I\/O) data of the controlled system and is a data-driven control method. The pseudo partial derivative (PPD) can be iteratively calculated through the parameter iterative update algorithm and reset algorithm to adjust the learning gain, solving the problem of strictly limited initial position of the traditional fixed learning gain iterative learning control (ILC). A linear combination of angle and angular velocity is introduced in the kinematic layer to avoid overshooting of the expected following target, and an iterative learning method is introduced in the dynamics to improve the accuracy. As the number of iterations increases, the steady-state error is gradually decreased. Finally, by comparing traditional proportional\u2013integral\u2013derivative (PID) simulations, the proposed algorithm\u2019s effectiveness and outstanding performance for the AUV heading tracking are confirmed.<\/jats:p>","DOI":"10.1177\/01423312241227539","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T04:22:10Z","timestamp":1707711730000},"page":"1503-1512","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Iterative learning\u2013based model-free adaptive precise heading following of an autonomous underwater vehicle with unknown disturbances"],"prefix":"10.1177","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3321-326X","authenticated-orcid":false,"given":"Donglei","family":"Dong","sequence":"first","affiliation":[{"name":"School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6215-9864","authenticated-orcid":false,"given":"Xianbo","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, China"},{"name":"The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, China"}]},{"given":"Jinjiang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China"}]},{"given":"Shaolong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, China"}]}],"member":"179","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2022.113300"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2743240"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20350"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/00207179.2018.1526414"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84882-730-1"},{"issue":"11","key":"e_1_3_2_7_1","first-page":"930","article-title":"Dynamic positioning of ship using backstepping controller with nonlinear disturbance observer","volume":"50","author":"Dong D","year":"2021","unstructured":"Dong D, Li J, Yang S, et al. 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