Nonlinear Model Predictive Control Design for BSM-MBR: Benchmark of Membrane Bioreactor

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Abstract

The optimal control and operation of a Membrane Bioreactor (MBR) process by Nonlinear Model Predictive Control (NMPC) is investigated in this work. First, the Benchmark Simulation Model for MBR (BSM-MBR) provided by Maere et al. (2011) to simulate a membrane bioreactor is extended to include a mathematical membrane fouling model where both reversible and irreversible fouling are taken into account. Then, an NMPC is designed by incorporating the nonlinear process model of BSM-MBR to control the dissolved oxygen concentration at certain level while meeting input and other process constraints. The performance of the NMPC is evaluated under both constant influent scenario and dynamic dry weather influent scenario. The simulation results demonstrate that NMPC works better in the constant influent case compared to the dynamic influent scenario.
Original languageEnglish (US)
Title of host publicationSubmitted to 21st IFAC World Congress
PublisherSubmitted to IFAC
StatePublished - 2020

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