Economic model predictive control of parabolic PDE systems using empirical eigenfunctions

Liangfeng Lao, Matthew Ellis, Antonios Armaou, Panagiotis D. Christofides

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This work focuses on the development of reduced-order models (ROMs) of transport-reaction processes described by nonlinear parabolic partial differential equations (PDEs) and their application in the formulation of economic model predictive control (EMPC) systems. Specifically, the reduced-order models of the PDEs are constructed on the basis of historical data-based empirical eigenfunctions by applying Karhunen-Loève expansion. Several EMPC systems each using a different ROM (i.e., different number of modes and derived from either using analytical sinusoidal/cosinusoidal eigenfunctions or empirical eigenfunctions as basis functions) are applied to a tubular reactor example where a second-order reaction occurs. The model accuracy, computational time and closed-loop economic performance of the closed-loop tubular reactor under the different EMPC systems are compared.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781479932726
StatePublished - 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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