Journal
JOURNAL OF PROCESS CONTROL
Volume 22, Issue 7, Pages 1171-1181Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2012.05.004
Keywords
Hybrid-neural modeling; Hybrid modeling; Semi-parametric modeling; Process control; Model Reference Control; Generic Model Control; Artificial Neural Networks
Funding
- Fundacao para a Ciencia e a Tecnologia [SFRH/BD/36990/2007]
- Fundação para a Ciência e a Tecnologia [SFRH/BD/36990/2007] Funding Source: FCT
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A general hybrid semi-parametric process control framework is proposed in this study. The motivation was the integration of different levels of knowledge systems into a general hybrid semi-parametric control structure, of which the general linear controller or the PID controller are, for instance, particular cases. Several hybrid semi-parametric control structure variants and tuning methods are benchmarked in relation to a simulated bioprocess control problem, namely closed-loop control of the biomass concentration through manipulation of the substrate feeding rate, coupled with the closed-loop control of the dissolved oxygen concentration through the stirring velocity. The results demonstrate that (i) due to the hybrid approach the control loop can be closed without any additional identification experiments; (ii) the incorporation of different types of knowledge can enhance the controller performance, when compared to structures without a priori knowledge; (iii) knowledge incorporation seems to facilitate the tuning of the controller; and (iv) the control action can be analyzed in relation to structural information incorporated into the hybrid controller. (C) 2012 Elsevier Ltd. All rights reserved.
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