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Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor
Joint Authors
Rómoli, Santiago
Serrano, Mario
Rossomando, Francisco
Vega, Jorge
Ortiz, Oscar
Scaglia, Gustavo
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-05
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies.
To address this issue, this work proposes an online state estimator based on a Radial Basis Function (RBF) neural network that operates in closed loop together with a control law derived on a linear algebra-based design strategy.
The proposed methodology is applied to a class of nonlinear systems with three types of uncertainties: (i) time-varying parameters, (ii) uncertain nonlinearities, and (iii) unmodeled dynamics.
To reduce the effect of uncertainties on the bioreactor, some integrators of the tracking error are introduced, which in turn allow the derivation of the proper control actions.
This new control scheme guarantees that all signals are uniformly and ultimately bounded, and the tracking error converges to small values.
The effectiveness of the proposed approach is illustrated on the basis of simulated experiments on a fed-batch bioreactor, and its performance is compared with two controllers available in the literature.
American Psychological Association (APA)
Rómoli, Santiago& Serrano, Mario& Rossomando, Francisco& Vega, Jorge& Ortiz, Oscar& Scaglia, Gustavo. 2017. Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor. Complexity،Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1143686
Modern Language Association (MLA)
Rómoli, Santiago…[et al.]. Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor. Complexity No. 2017 (2017), pp.1-16.
https://search.emarefa.net/detail/BIM-1143686
American Medical Association (AMA)
Rómoli, Santiago& Serrano, Mario& Rossomando, Francisco& Vega, Jorge& Ortiz, Oscar& Scaglia, Gustavo. Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor. Complexity. 2017. Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1143686
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143686