{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:06:05Z","timestamp":1773414365356,"version":"3.50.1"},"reference-count":0,"publisher":"World Scientific Pub Co Pte Ltd","issue":"08","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:p> In the present work, an indirect adaptive neural control method for nonlinear systems having unknown dynamics is proposed. The proposed control architecture is composed by a neural emulator (NE) and a neural controller (NC) where a new decoupled variable learning rates (VLRs) combined with Taylor development (TD) are used to train the NE and the NC. The developed VLRs mixed with the TD (TDVLRs) ensure a quick adaptation of neural networks parameters guaranteeing a faster output convergence and reducing the tracking error. The effectiveness of the proposed TDVLRs is illustrated by simulation with a nonlinear dynamic system. In order to validate simulation results, an application on a transesterification reactors is, also, presented. <\/jats:p>","DOI":"10.1142\/s0218213022500415","type":"journal-article","created":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T16:19:40Z","timestamp":1663604380000},"source":"Crossref","is-referenced-by-count":6,"title":["A New Indirect Adaptive Neural Control for Nonlinear Systems: A Real Validation on a Chemical Process"],"prefix":"10.1142","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4000-8413","authenticated-orcid":false,"given":"Rabab","family":"Hamza","sequence":"first","affiliation":[{"name":"Research Laboratory of Numerical Control of Industrial Processes, National Engineering School of Gabes, University of Gabes, Omar Ibn Khattab Street 6029, Gabes, Tunisia"}]},{"given":"Yassin","family":"Farhat","sequence":"additional","affiliation":[{"name":"Research Laboratory of Numerical Control of Industrial Processes, National Engineering School of Gabes, University of Gabes, Omar Ibn Khattab Street 6029, Gabes, Tunisia"}]},{"given":"Ali","family":"Zribi","sequence":"additional","affiliation":[{"name":"Research Laboratory of Numerical Control of Industrial Processes, National Engineering School of Gabes, University of Gabes, Omar Ibn Khattab Street 6029, Gabes, Tunisia"}]}],"member":"219","published-online":{"date-parts":[[2022,12,28]]},"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213022500415","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T11:50:48Z","timestamp":1672314648000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0218213022500415"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12]]},"references-count":0,"journal-issue":{"issue":"08","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["10.1142\/S0218213022500415"],"URL":"https:\/\/doi.org\/10.1142\/s0218213022500415","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12]]},"article-number":"2250041"}}