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 H 2 recovery while achieving a closed loop product H 2 purity of 99.99%, for separating 70% H 2 , 30% CH 4 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.