{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T10:29:25Z","timestamp":1747823365712,"version":"3.40.5"},"reference-count":16,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Shandong Provincial Natural Science Foundation","doi-asserted-by":"crossref","award":["ZR2019BEE066","19-6-2-68-cg"],"award-info":[{"award-number":["ZR2019BEE066","19-6-2-68-cg"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100019598","name":"Applied Basic Research Project of Qingdao","doi-asserted-by":"crossref","award":["ZR2019BEE066","19-6-2-68-cg"],"award-info":[{"award-number":["ZR2019BEE066","19-6-2-68-cg"]}],"id":[{"id":"10.13039\/501100019598","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2022,1,11]]},"abstract":"<jats:p>Although solving the robust control problem with offline manner has been studied, it is not easy to solve it using the online method, especially for uncertain systems. In this paper, a novel approach based on an online data-driven learning is suggested to address the robust control problem for uncertain systems. To this end, the robust control problem of uncertain systems is first transformed into an optimal problem of the nominal systems via selecting an appropriate value function that denotes the uncertainties, regulation, and control. Then, a data-driven learning framework is constructed, where Kronecker\u2019s products and vectorization operations are used to reformulate the derived algebraic Riccati equation (ARE). To obtain the solution of this ARE, an adaptive learning law is designed; this helps to retain the convergence of the estimated solutions. The closed-loop system stability and convergence have been proved. Finally, simulations are given to illustrate the effectiveness of the method.<\/jats:p>","DOI":"10.1155\/2022\/9686060","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T23:35:26Z","timestamp":1641944126000},"page":"1-9","source":"Crossref","is-referenced-by-count":2,"title":["Adaptive Robust Control for Uncertain Systems via Data-Driven Learning"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2908-2583","authenticated-orcid":true,"given":"Jun","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3842-9107","authenticated-orcid":true,"given":"Qingliang","family":"Zeng","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China"},{"name":"Department of Information Science and Engineering, Shandong Normal University, Jinan 250358, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1080\/00207179208934374"},{"key":"2","article-title":"Essentials of robust control","volume":"38","author":"K. 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