Lyapunov-based Economic Model Predictive Control with Taylor Series State Approximations

Abstract

A method for integrating optimization and control during on-line process operation is known as economic model predictive control (EMPC). EMPC optimizes a general cost function which reflects process economics subject to a model of the process. One formulation of EMPC which can maintain closed-loop stability in the presence of sufficiently small disturbances is Lyapunov-based EMPC (LEMPC). In this work, we make precise connections between closed-loop stability considerations under LEMPC and numerical approximations (via Taylor series) of the solution of the nonlinear dynamic model of the process used in the controller. A chemical process example is utilized to demonstrate the concepts developed.