Two-stage anaerobic digestion (AD)
processes have been proposed
to improve the operation of conventional single-stage AD systems.
In this study, both standard and robust nonlinear model predictive
controllers (NMPCs) were applied to a two-stage AD process treating
tequila vinasses. NMPC provides a systematic methodology to handle
nonlinearities and constraints on the manipulated and controlled variables,
which are commonly found in the two-stage AD processes. In contrast,
the robust NMPC framework aims to determine the control actions that
minimize the offsets in the controlled variables while taking into
account uncertainties that are likely to occur in the process, leading
to the poor performance of the standard NMPC controller. Results showed
an acceptable and superior closed-loop performance of the proposed
robust NMPC controller with respect to the standard NMPC in the presence
of disturbances in the inlet streams and set-point changes, including
uncertainties.
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