Optimization and Control of Pressure Swing Adsorption Processes Under Uncertainty

The real-time periodic performance of a pressure swing adsorption (PSA) system strongly depends on the choice of key decision variables and operational considerations such as processing steps and column pressure temporal profiles, making its design and operation a challenging task. This work presents a detailed optimization-based approach for simultaneously incorporating PSA design, operational, and control aspects under the effect of time variant and invariant disturbances. It is applied to a two-bed, six-step PSA system represented by a rigorous mathematical model, where the key optimization objective is to maximize the expected H2 recovery while achieving a closed loop product H2 purity of 99.99%, for separating 70% H2, 30% CH4 feed. The benefits over sequential design and control approach are shown in terms of closed-loop recovery improvement of more than 3%, while the incorporation of explicit/multiparametric model predictive controllers improves the closed loop performance. © 2012 American Institute of Chemical Engineers (AIChE).