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dc.contributor.authorFonseca R.R.
dc.contributor.authorSencio R.R.
dc.contributor.authorFranco I.C.
dc.contributor.authorDa Silva F.V.
dc.date.accessioned2019-08-20T00:12:13Z
dc.date.available2019-08-20T00:12:13Z
dc.date.issued2018
dc.identifier.citationFONSECA, RODOLPHO RODRIGUES; SENCIO, RAFAEL RIBEIRO; FRANCO, Ivan Carlos; DA SILVA, FLÁVIO VASCONCELOS. An Adaptive Fuzzy Feedforward-Feedback Control System Applied to a Saccharification Process. CHEMICAL PRODUCT AND PROCESS MODELING, v. 13, n. 0, p. 1-1, 2018.
dc.identifier.issn1934-2659
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1854
dc.description.abstract© 2018 Walter de Gruyter GmbH, Berlin/Boston.In industrial bioprocess control, disturbance sources typically influences process variable regulation. These disturbances may reduce a system control performance or even affect the final bioproduct quality. Therefore, feedforward control is desired because it anticipates the effects caused by these disturbances in an attempt to keep the process variable at the setpoint value. However, designing a feedforward control law requires process modeling, which can be a tough task when dealing with bioprocesses that are intrinsically nonlinear and multivariable systems. Thus, an adaptive feedforward control law or other advanced control system is needed for satisfactory disturbance rejection. For this reason, a general fuzzy feedforward control system is proposed in this paper to replace the classical feedforward control, making it easier to implement the feedforward control action by avoiding nonlinear and multivariable process modeling. The adaptive fuzzy feedforward-feedback (A4FB) system was applied to a product concentration control loop in an enzymatic reactor, to reject disturbances caused by variations in the substrate and enzymatic solutions feed concentration. The results showed that the A4FB controller rejected much more disturbance effects than classical feedforward control law, demonstrating its advantage, supported by not only its simple implementation, but also its improved disturbance rejection.
dc.relation.ispartofChemical Product and Process Modeling
dc.rightsAcesso Restrito
dc.titleAn adaptive fuzzy feedforward-feedback control system applied to a saccharification process
dc.typeArtigo


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