Document Type
Conference Proceeding
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.
Disciplines
Controls and Control Theory | Process Control and Systems
Recommended Citation
K. K. Rangan and H. Durand, "Lyapunov-based Economic Model Predictive Control with Taylor Series State Approximations," 2020 American Control Conference (ACC), Denver, CO, USA, 2020, pp. 1980-1985, doi: 10.23919/ACC45564.2020.9147987.
Comments
© American Automatic Control Council (AACC) 2020. Peer Reviewed Conference Proceeding, 2020 American Control Conference (ACC), July 1-3, 2020, Denver, CO, USA. Originally published at https://doi.org/10.23919/ACC45564.2020.9147987. Financial support from the Air Force Office of Scientific Research is gratefully acknowledged. This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-19-1-0059.