Model predictive control (MPC) has been an important and successful advanced control technology in process industries mainly due to its ability to handle effectively complex systems with hard control constraints. MPC presents a very flexible optimal control framework that can handle a wide range of industrial issues while incorporating state or output feedback. Traditionally, MPC with quadratic cost functions had dominated the focus of MPC research. Advances in technologies in the last decades have enabled us to look beyond the traditional MPC and brought new challenges and opportunities in MPC research. One important example of this technology-driven development is economic MPC.
Economic MPC removes the separation between optimization and control in the traditional hierarchical real-time optimization systems and addresses both optimization and control in one single layer. Economic MPC optimizes a general economic cost function, which in general is not quadratic. This workshop is intended to introduce researchers to (i) the theory and design of economic MPC systems, (ii) numerical implementation of economic MPC, and (iii) applications of economic MPC to different systems.