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Optimal structure of learning - type set - point in various set - point - related indirect ILC algorithms / Youqing Wang in Industrial & engineering chemistry research, Vol. 50 N° 23 (Décembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 23 (Décembre 2011) . - pp. 13427–13434 Titre : Optimal structure of learning - type set - point in various set - point - related indirect ILC algorithms Type de document : texte imprimé Auteurs : Youqing Wang, Auteur ; Jianyong Tuo, Auteur ; Zhong Zhao, Auteur Année de publication : 2012 Article en page(s) : pp. 13427–13434 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Optimal Résumé : According to the literature statistics, only less than 10% of reported iterative learning control (ILC) methods have been devoted to the indirect approach. Motivated by the full potential of research opportunities in this field, a number of studies on indirect ILC were proposed recently, where ILC-based P-type control and learning-type model predictive control (L-MPC) are two successful stories. All indirect ILC algorithms consist of two loops: an ILC in the outer loop and a local controller in the inner loop. The local controllers are, respectively, a P-type controller in the ILC-based P-type control and a model predictive control (MPC) in the L-MPC. Logically, this leads to the question of what type of ILC should be chosen respectively for the two above-mentioned indirect ILC methods. In this study, P-type ILC and anticipatory P-type (A-P-type) ILC are studied and compared, because they are typical and widely implemented. Based on mathematical analysis and simulation test, it has been proved that the A-P-type ILC should be used in the ILC-based P-type control and while the P-type ILC should be used in the L-MPC. Furthermore, an improved L-MPC with batch-varying learning gain was proposed to handle the trade-off between convergence rate and robustness performance. The simulation results on injection molding process and a nonlinear batch process validated the feasibility and effectiveness of the proposed algorithm. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie200021t [article] Optimal structure of learning - type set - point in various set - point - related indirect ILC algorithms [texte imprimé] / Youqing Wang, Auteur ; Jianyong Tuo, Auteur ; Zhong Zhao, Auteur . - 2012 . - pp. 13427–13434. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 23 (Décembre 2011) . - pp. 13427–13434 Mots-clés : Optimal Résumé : According to the literature statistics, only less than 10% of reported iterative learning control (ILC) methods have been devoted to the indirect approach. Motivated by the full potential of research opportunities in this field, a number of studies on indirect ILC were proposed recently, where ILC-based P-type control and learning-type model predictive control (L-MPC) are two successful stories. All indirect ILC algorithms consist of two loops: an ILC in the outer loop and a local controller in the inner loop. The local controllers are, respectively, a P-type controller in the ILC-based P-type control and a model predictive control (MPC) in the L-MPC. Logically, this leads to the question of what type of ILC should be chosen respectively for the two above-mentioned indirect ILC methods. In this study, P-type ILC and anticipatory P-type (A-P-type) ILC are studied and compared, because they are typical and widely implemented. Based on mathematical analysis and simulation test, it has been proved that the A-P-type ILC should be used in the ILC-based P-type control and while the P-type ILC should be used in the L-MPC. Furthermore, an improved L-MPC with batch-varying learning gain was proposed to handle the trade-off between convergence rate and robustness performance. The simulation results on injection molding process and a nonlinear batch process validated the feasibility and effectiveness of the proposed algorithm. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie200021t