| Titre : | Combining kernel partial least - squares modeling and iterative learning control for the batch - to - batch optimization of constrained nonlinear processes (2010) |
| Auteurs : | Yingwei Zhang, Auteur ; Yunpeng Fan, Auteur ; Pengchao Zhang, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Industrial & engineering chemistry research (Vol. 49 N° 16, Août 2010) |
| Article en page(s) : | pp. 7470–7477 |
| Note générale : | Industrial chemistry |
| Langues : | Anglais |
| Tags : | 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 |
