Identification and Model Predictive Control (MPC) of Aqueous Polyvinyl Alcohol Degradation in UV/H2O2 Photochemical Reactors.

The performance of two continuous UV/H₂O₂ photoreactors in series under unsteady-state condition is studied. An input–output dynamic model is constructed to describe the degradation of water-soluble polyvinyl alcohol (PVA) in photoreactors. Identification techniques, AutoRegressive with eXogenous input (ARX) and AutoRegressive Moving Average with eXogenous input (ARMAX), are employed to construct transfer functions. The simulation is carried out for an open-loop operation by applying step changes to the input variables (PVA and H₂O₂ inlet concentrations and PVA feed flow rate) using the developed model. For effluent total organic carbon (TOC) and H₂O₂ concentrations as responses, a model predictive control (MPC) scheme is developed to control the photoreactors to maintain desired values of process variables for setpoint and load changes. The closed-loop simulation results show that the multi-input/multi-output (MIMO) MPC produce a good performance for tracking setpoint changes in the TOC and H₂O₂ concentrates at the photoreactor effluent and it is also able to handle process interactions and constraints. The MPC controller successfully suppresses stochastic disturbances of the inlet PVA concentration. [ABSTRACT FROM AUTHOR]