Research On Oxygen Production Via VPSA Optimized Based On MPC Control Strategy

A systematical study on oxygen production via vacuum pressure swing adsorption was carried out in this paper,mainly started with simulation,optimization,and the designing of the model predictive controller.On the one hand,a two-bed six-step separation process was established in the gPROMS software and was experimentally verified by experimental approach.On the one hand,sequential secondary optimization was adopted to optimize the VPSA process based on the simulation verification.After the process reaches the optimal operating state,the MPC controller was then designed using the state space model,and the disturbances which may exist in the actual industry were introduced into the system to evaluate the performance of the model predictive controller.First of all,a mathematical model library,boundary conditions,and evaluation indicators that were suitable for the process were selected and established in the g PROMS software according to the characteristics of the VPSA process.And then,a mathematical model of two-bed six-step VPSA process for air separation was established.LiLSX molecular sieve was adopted as the adsorbent and via the comparison of experimental results and simulation results,the rationality of the model library and simulation process was verified.Then sequential secondary optimization method was used to make the process run to the optimal state.After optimization,the purity and recovery rate of oxygen in the product gas was optimized from 90.2%/58.7%before optimization to 92.03%/60.5%respectively.Energy consumption per unit product has also been reduced from 0.42 kWh·m^-3 to 0.31 kWh·m^-3.Changes before and after the optimization were analyzed via the axial distribution of nitrogen inside the tower at each step.Most of the current research in the field of oxygen production is focused on miniaturization and rapid oxygen production.However,there is no research on the optimization control of the oxygen production process.The research in this paper was carried out on the basis of its own model,experimental verification and optimization calculation.Based on the above,the concentration of oxygen in the product gas was selected as the control target and the duration of the adsorption step was chosen as the controlled variable of the designed controller.The design work of model predictive controller was discussed and studied from three aspects which include the predictive model construction,feedback mechanism and rolling optimization strategy.Among them,the construction of the prediction model was carried out from three aspects which include the data collection,model identification and model checking respectively.And finally,the eighth-order state space model was selected as the prediction model.Subsequently,two unstable disturbances that may exist in actual production were introduced into the stable operation VPSA process,and the influence of the introduced disturbance on the process was studied and analyzed.The designed model predictive controller was then introduced into the system and the performance of the process under open-loop and closed-loop conditions was compared and analyzed on this basis to verify the effectiveness of the predictive model.The results show that the designed model predictive controller can effectively resist the influence of external disturbances for the VPSA system to produce 92%oxygen.