Design of integrated real time optimization and model predictive control for distillation column

To present the design of the integrated real time optimization (RTO) and model predictive control (MPC) with application to distillation column. The integration of the RTO and MPC can be divided into two structures, namely, the 2-layer and 3-layer structures. In the control hierarchy, the RTO layer optimizes the plant operating conditions based on an economic function. The optimal set points of the RTO layer are transfered to the MPC layer which aims to regulate the process variables at the optimal set points. The MPC employs the finite horizon control design based on the state-space model. This thesis consists of two main parts. In the first part, we propose a design of the integrated RTO and nominal MPC for the distillation column. The design is based on the nominal model of the distillation column. The simulation results illustrate the effectiveness of the proposed design methods. In the second part, we extend the design framework to cope with the uncertainty of the process. Thus, we propose a design of the integration of RTO and multiple MPC for the distillation column. The process dynamic is described by a set of models, where each model corresponds with a specific operating range of the distillation column. We compare the simulation results of the multiple MPC with that of the nominal MPC to determine advantages and disadvantages of each method.