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Combining kernel partial least - squares modeling and iterative learning control for the batch - to - batch optimization of constrained nonlinear processes / Yingwei Zhang in Industrial & engineering chemistry research, Vol. 49 N° 16 (Août 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 16 (Août 2010) . - pp. 7470–7477 Titre : Combining kernel partial least - squares modeling and iterative learning control for the batch - to - batch optimization of constrained nonlinear processes Type de document : texte imprimé Auteurs : Yingwei Zhang, Auteur ; Yunpeng Fan, Auteur ; Pengchao Zhang, Auteur Année de publication : 2010 Article en page(s) : pp. 7470–7477 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Non  linear  system  Optimization  Batchwise  Learning  Modeling  Partial  least  squares Résumé : A new approach to the optimal control with constraints is proposed to achieve a desired end product quality, and a modified kernel partial least-squares (KPLS) is used to build the combining model of nonlinear processes. The particle swarm optimization algorithm is used to solve the optimal problem. The contributions of the article are as follows: The modified KPLS is proposed for the optimal control purpose, and the optimal manipulated variables are computed for the next batch run based on modified KPLS. The proposed approach is applied to a bulk polymerization of styrene batch process and fused magnesium furnace. Simulation results show the proposed approach is effective for predicting the control profile of next batch run. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23109320 [article] Combining kernel partial least - squares modeling and iterative learning control for the batch - to - batch optimization of constrained nonlinear processes [texte imprimé] / Yingwei Zhang, Auteur ; Yunpeng Fan, Auteur ; Pengchao Zhang, Auteur . - 2010 . - pp. 7470–7477. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 16 (Août 2010) . - pp. 7470–7477 Mots-clés : Non  linear  system  Optimization  Batchwise  Learning  Modeling  Partial  least  squares Résumé : A new approach to the optimal control with constraints is proposed to achieve a desired end product quality, and a modified kernel partial least-squares (KPLS) is used to build the combining model of nonlinear processes. The particle swarm optimization algorithm is used to solve the optimal problem. The contributions of the article are as follows: The modified KPLS is proposed for the optimal control purpose, and the optimal manipulated variables are computed for the next batch run based on modified KPLS. The proposed approach is applied to a bulk polymerization of styrene batch process and fused magnesium furnace. Simulation results show the proposed approach is effective for predicting the control profile of next batch run. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23109320