Nonlinear model predictive control of industrial type IV fluid catalytic cracking (FCC) units for maximum gasoline yield

This paper addresses the problem of stabilizing the operation of an industrial type IV fluid catalytic cracking unit (FCCU) around an unstable high gasoline yield operating steady state. The model used in the work has been previously checked successfully against a number of industrial units. The stabilization is achieved through simulated implementation of a model predictive control (MPC) version that utilizes the nonlinear model in the output prediction. A state estimation technique is also incorporated in the MPC algorithm to improve the latter performance in the presence of unmeasured disturbances and/or parametric modeling errors. Two types of closed-loop simulations were tested, namely, servo and regulator problems. The results of the simulation illustrated that operating the FCCU at the unstable region is possible due to the effectiveness of MPC in handling such a problem. It is also found that, for an open-loop unstable process, state estimation must be used to improve the feedback response of MPC in the presence of unmeasured disturbances or modeling errors. Traditional PI control was also examined for the FCCU stabilization control problem, and its performance is compared with that of the NLMPC. The investigation revealed that reasonable PI performance can also be obtained through careful tuning of its settings and that NLMPC is considered easier to apply in that case.