Title: Control of nonlinear dynamical systems modeled by recurrent neural networks
Abstract:AIChE JournalVolume 39, Issue 11 p. 1890-1894 Process Systems Engineering Control of nonlinear dynamical systems modeled by recurrent neural networks Michael Nikolaou, Corresponding Author Michael Nik...AIChE JournalVolume 39, Issue 11 p. 1890-1894 Process Systems Engineering Control of nonlinear dynamical systems modeled by recurrent neural networks Michael Nikolaou, Corresponding Author Michael Nikolaou Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Search for more papers by this authorVijaykumar Hanagandi, Vijaykumar Hanagandi Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Search for more papers by this author Michael Nikolaou, Corresponding Author Michael Nikolaou Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Search for more papers by this authorVijaykumar Hanagandi, Vijaykumar Hanagandi Dept. of Chemical Engineering, Texas A&M University, College Station, TX 77843Search for more papers by this author First published: November 1993 https://doi.org/10.1002/aic.690391116Citations: 25AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume39, Issue11November 1993Pages 1890-1894 RelatedInformationRead More
Publication Year: 1993
Publication Date: 1993-11-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 33
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