(772b) Economic Cost Function Design and Model Predictive Control of a Chemical Process Network | AIChE

(772b) Economic Cost Function Design and Model Predictive Control of a Chemical Process Network

Authors 

Chen, X. - Presenter, Univ. of California, Los Angeles
Heidarinejad, M. - Presenter, University of California, Los Angeles
Liu, J. - Presenter, University of California, Los Angeles


Maximizing profit has been and will always be the primary purpose of optimal process operation. Within process control, the economic optimization considerations of a plant are usually addressed via a real-time optimization (RTO) system. In general, an RTO system includes two different layers: the upper layer that optimizes process operation set-points taking into account economic considerations using steady-state system models, and the lower layer (i.e., process control layer) whose primary objective is to employ feedback control systems to force the process to track the set-points. In the past years, there have been several attempts to integrate MPC and economic optimization of processes. In particular, in our recent work [1], we developed Lyapunov-based economic MPC (LEMPC) designs which are capable of optimizing closed-loop performance with respect to general economic considerations for nonlinear systems. The design of the LEMPC is based on uniting receding horizon control with explicit Lyapunov-based nonlinear controller design techniques and allows for an explicit characterization of the stability region of the closed-loop system.

In the present work, we focus on the application of the theoretical results developed in [1] to a catalytic alkylation of benzene process network, which consists of four continuous stirred tank reactors and a flash separator. In the design of the economic cost function of the LEMPC, we take into three aspects. First, we try to maximize the production of the product ethylbenzene and minimize the production of the by-product 1,3-diethylbenzene. To account for this aspect, the reaction rates of the reactions in the reactors are involved in the cost function in an appropriate form. Second, we want to improve the quality of the separation process which is directly related to the quality of the product. The last aspect we consider is to reduce the energy consumption of the distillation column. This consideration is based on the fact that the reactions take place in the reactors are exothermic and the distillation column consumes most of the energy of the process. Based on this economic cost function, we design the LEMPC for the alkylation process network. Extensive simulations are carried out to compare the LEMPC with a traditional model predictive control design using a quadratic cost function, from stability and performance points of view.

[1] M. Heidarinejad, J. Liu and P. D. Christofides, "Economic Model Predictive Control of Nonlinear Process Systems Using Lyapunov Techniques," AIChE Journal, in press.

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