Multi-scale aspects in model-predictive control

George Stephanopoulos, Orhan Karsligil, Matthew Dyer

Research output: Contribution to journalConference articlepeer-review

23 Scopus citations


Multi-scale models of processing systems offer an attractive alternative to models defined in the time- or frequency-domain. They are defined on dyadic or higher-order trees, whose nodes are used to index the values of any variable, localized in both time and scale (range of frequencies). This dual localization is particularly attractive in solving estimation and control problems. In this paper, multi-scale models are used to design model-predictive controllers (MPC), resulting in design techniques with several important advantages, such as; (a) natural depiction of performance characteristics and treatment of output constraints, (b) fast algorithms for establishing the constrained control policies over long prediction/control horizons, (c) rich depiction of feedback errors at several scales, and (d) optimal fusion of multi-rate measurements and control actions..

Original languageEnglish (US)
Pages (from-to)275-282
Number of pages8
JournalJournal of Process Control
Issue number2
StatePublished - Apr 2000
Externally publishedYes
EventThe 5th IFAC Symposium on the Dynamics and Control of Process Systems (DYCOPS-5) - Corfu, Greece
Duration: Jun 8 1998Jun 10 1998

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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