Model Predictive Control for Efficient Process Control: A Case Study for Absorber-Stripper System with MEA in Hydrogen Plant
Keywords:
Carbon Capture, Process Control, Model Predictive Control, MonoethanolamineAbstract
Control mechanisms are essential for all operations in chemical processing facilities, including the absorber-stripper system. This system, which is utilized for CO2 capture, is a common feature in hydrogen plants that use steam-methane reforming technology to purify their flue gas (post- combustion). The primary objective of this system is to maximize CO2 recovery in a cost-effective manner. Given the dynamic nature of plant operations, with frequent changes in production capacity, a robust controller is crucial for maintaining system stability. Model Predictive Control (MPC) is a widely used control method. This study focuses on developing a control simulation for an absorber- stripper system using monoethanolamine solution (MEA) and implementing it with MPC. The steady- state system is designed using Aspen Plus and integrated with MATLAB/Simulink to construct a multi- input-multi-output controller with MPC. The simulation aims to regulate the CO2 recovery within a specific range of input disturbances while ensuring that the system operates within acceptable operating conditions. This is achieved by controlling all potential manipulated variables, such as flow of MEA solution to both absorber and stripper, flow of cooling and heating agent, and make up water. A comparison with the traditional PID control approach is also presented as part of this research. It is concluded from the result that MPC Controller is superior than PID. The MPC controller exhibits superior performance by having less settling time. This is accomplished by effectively minimizing transient deviations from the desired output.
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