Abstract

The traditional approach to optimal economic operation of industrial processes has been the use of a hierarchically structured control system. This hierarchical structure comprises a steady state optimization layer, that computes optimal static operating points for the system, and a dynamic model predictive control (MPC) layer, that ensures the system stays near these operating points. However, with this translation of economic objectives to control objectives, it is possible that the process is not being optimally dynamically operated. Economic MPC , where the economics of the process is optimized directly, has been recently proposed to overcome the possible `sub-optimality’ of the hierarchical architecture.

This talk will focus on issues relating to the asymptotic stability of the closed-loop system resulting from the use of an economic MPC design, practicalities involved in setting up the dynamic economic optimization problem associated with economic MPC and a possible redesign of the hierarchical structure that incorporates the economics of the process in the dynamic optimization.