Economic model predictive control with time‐varying objective function for nonlinear process systems |
| |
| Authors: | Matthew Ellis Panagiotis D. Christofides |
| |
| Affiliation: | 1. Dept. of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA;2. Dept. of Electrical Engineering, University of California, Los Angeles, CA |
| |
| Abstract: | Economic model predictive control (EMPC) is a control scheme that combines real‐time dynamic economic process optimization with the feedback properties of model predictive control (MPC) by replacing the quadratic cost function with a general economic cost function. Almost all the recent work on EMPC involves cost functions that are time invariant (do not explicitly account for time‐varying process economics). In the present work, we focus on the development of a Lyapunov‐based EMPC (LEMPC) scheme that is formulated with an explicitly time‐varying economic cost function. First, the formulation of the proposed two‐mode LEMPC is given. Second, closed‐loop stability is proven through a theoretical treatment. Last, we demonstrate through extensive closed‐loop simulations of a chemical process that the proposed LEMPC can achieve stability with time‐varying economic cost as well as improve economic performance of the process over a conventional MPC scheme. © 2013 American Institute of Chemical Engineers AIChE J 60: 507–519, 2014 |
| |
| Keywords: | process control optimization |
|
|
