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Complexity
Volume 2017 (2017), Article ID 9391879, 16 pages
https://doi.org/10.1155/2017/9391879
Research Article

Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor

1Instituto de Ingeniería Química, Universidad Nacional de San Juan, CONICET, Av. Lib. San Martín Oeste, 1109 San Juan, Argentina
2Instituto de Automática, Universidad Nacional de San Juan, CONICET, Av. Lib. San Martín Oeste, 1109 San Juan, Argentina
3Facultad Regional Santa Fe, Universidad Tecnológica Nacional, CONICET, Lavaisse 610, Santa Fe, Argentina
4Instituto de Desarrollo Tecnológico para la Industria Química (INTEC (UNL-CONICET)), Güemes, 3450 Santa Fe, Argentina

Correspondence should be addressed to Mario Serrano; ra.ude.jsnu.if@onarrese

Received 15 June 2017; Accepted 9 July 2017; Published 5 September 2017

Academic Editor: Chenguang Yang

Copyright © 2017 Santiago Rómoli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, and Gustavo Scaglia, “Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor,” Complexity, vol. 2017, Article ID 9391879, 16 pages, 2017. doi:10.1155/2017/9391879