{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T19:40:40Z","timestamp":1768074040125,"version":"3.49.0"},"reference-count":26,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T00:00:00Z","timestamp":1718841600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This study focuses on generating reliable signals from measured noisy signals through an enhanced sensor fusion method. The main contribution of this research is the development of a novel sensor fusion architecture that creates virtual sensors, improving the system\u2019s redundancy. This architecture utilizes an input observer to estimate the system input, then it is introduced to the system model, the output of which is the virtual sensor. Then, this virtual sensor includes two filtering stages, both derived from the system\u2019s dynamics\u2014the input observer and the system model\u2014which effectively diminish noise in the virtual sensors. Afterwards, the same architecture includes a classical sensor fusion scheme and a voter to merge the virtual sensors with the real measured signals, enhancing the signal reliability. The effectiveness of this method is shown by applying merged signals to two distinct diagnosers: one utilizes a high-order sliding mode observer, while the other employs an innovative extension of a predefined-time observer. The findings indicate that the proposed architecture improves diagnostic results. Moreover, a three-wheeled omnidirectional mobile robot equipped with noisy sensors serves as a case study, confirming the approach\u2019s efficacy in an actual noisy setting and highlighting its principal characteristics. Importantly, the diagnostic systems can manage several simultaneous actuator faults.<\/jats:p>","DOI":"10.3390\/a17060270","type":"journal-article","created":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T03:46:29Z","timestamp":1718855189000},"page":"270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Sensor Fusion Architecture for Fault Diagnosis with a Predefined-Time Observer"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0099-8822","authenticated-orcid":false,"given":"Ofelia","family":"Begovich","sequence":"first","affiliation":[{"name":"Cinvestav del IPN, Unidad Guadalajara, Av. del Bosque 1145, Zapopan Jalisco C.P. 45019, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9131-2402","authenticated-orcid":false,"given":"Adri\u00e1n","family":"Liz\u00e1rraga","sequence":"additional","affiliation":[{"name":"Cinvestav del IPN, Unidad Guadalajara, Av. del Bosque 1145, Zapopan Jalisco C.P. 45019, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3028-3446","authenticated-orcid":false,"given":"Antonio","family":"Ram\u00edrez-Trevi\u00f1o","sequence":"additional","affiliation":[{"name":"Cinvestav del IPN, Unidad Guadalajara, Av. del Bosque 1145, Zapopan Jalisco C.P. 45019, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1002\/asjc.2854","article-title":"Active fault detection and isolation in linear time-invariant systems: A geometric approach","volume":"25","author":"Begovich","year":"2023","journal-title":"Asian J. 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