Performance evaluation of the fast model predictive control scheme on a CO2 capture plant through absorption/stripping system

Abstract

The Classical Model Predictive Control (CMPC) has the drawback of slow response in complex dynamic systems. In this work, the Fast Model Predictive Control (FMPC), which accelerates the computation time through the fragmental solution of a complex quadratic program (QP), is investigated as a possible alternative to control the standard CO2 capture plant using MEA with various step changes. Aspen PLUS® and MATLAB® a are utilized to implement the control strategy. The study concluded that the FMPC controller has an average settling time of 51.42 s for all step changes, which is 74.8% faster than the CMPC. The average IAE value for FMPC was approximately 0.1307 which is 59 times smaller than the CMPC controller. Additionally, the ISE and ITSE values demonstrated much improved outcomes for the FMPC controller. The offsets for the FMPC are maintained at negligible levels through suitable tunning since offsets are the main hurdle observed when the FMPC controller is implemented on chemical process systems.