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First, according to the periodic repetitive working characteristics of autonomous buses, a novel dynamic linearized method used in the iterative domain is utilized, and a time-varying data model with a pseudo gradient (PG) is given. Then, the R-MFAILC controller is designed with a proposed adaptive attenuation factor. The proposed algorithm's advantage lies in the R-MFAILC controller, which solely utilizes the input and output data of the regulated entity. Moreover, the R-MFAILC controller has strong robustness and can handle the nonlinear measurement disturbances of the system. In simulations based on the Truck-Sim simulation platform, the effectiveness of the proposed algorithm is verified. A rigorous mathematical analysis is employed to demonstrate the stability and convergence of the proposed algorithm.<\/jats:p>","DOI":"10.1177\/00368504241249617","type":"journal-article","created":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T11:22:15Z","timestamp":1716549735000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Robust model-free adaptive iterative learning control for an autonomous bus trajectory tracking system"],"prefix":"10.1177","volume":"107","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0031-9359","authenticated-orcid":false,"given":"Shida","family":"Liu","sequence":"first","affiliation":[{"name":"The School of Electrical and Control Engineering, The North China University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Huang","sequence":"additional","affiliation":[{"name":"The School of Electrical and Control 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