{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:35:54Z","timestamp":1760142954102,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T00:00:00Z","timestamp":1704844800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan of China","award":["2018AAA0101000","62076028"],"award-info":[{"award-number":["2018AAA0101000","62076028"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2018AAA0101000","62076028"],"award-info":[{"award-number":["2018AAA0101000","62076028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Due to the complexity of digital equipment and systems, it is quite difficult to obtain a precise mechanism model in practice. For an unknown discrete-time nonlinear system, in this paper, a semi-parametric model is used to describe this discrete-time nonlinear system, and this semi-parametric model contains a parametric uncertainty part and a nonparametric uncertainty part. Based on this semi-parametric model, a novel data-driven control algorithm based on an information concentration estimator and regularized online sequential extreme learning machine (ReOS-ELM) is designed. The information concentration estimator estimates the parametric uncertainty part; The training data of ReOS-ELM network is obtained, based on symmetry and information concentration estimator, then the training of ReOS-ELM network and the estimate of nonparametric uncertainty part using ReOS-ELM network are carried out online, successively. A stability analysis and three simulation examples were performed, and the simulation results show that the proposed data-driven control algorithm is effective in improving the control accuracy.<\/jats:p>","DOI":"10.3390\/sym16010088","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T05:24:12Z","timestamp":1704950652000},"page":"88","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Data-Driven Control Based on Information Concentration Estimator and Regularized Online Sequential Extreme Learning Machine"],"prefix":"10.3390","volume":"16","author":[{"given":"Xiaofei","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Vehicle and Mobility, Tsinghua University, Haidian District, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbin","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology, Beijing 100084, China"},{"name":"National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1109\/TCST.2010.2093136","article-title":"A novel data-driven control approach for a class of discrete-time nonlinear systems","volume":"19","author":"Hou","year":"2011","journal-title":"IEEE Trans. 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