A Two-Level Model Predictive Control Formulation for Stabilization and Optimization

Zhaoyang Wan, Mayuresh V. Kothare

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


In this paper, we present a novel MPC algorithm, which has a two-level hierarchical structure. For the lower level control objective of stabilization, no optimization is involved, making it computationally efficient. For the higher level control objective of achieving an economic target, on-line optimization is performed with any desired objective function and control horizon without affecting the stability of the closed-loop system. This higher level optimization problem does not have to be solved within one sampling period, making the overall algorithm computationally attractive. The proposed two-level algorithm is illustrated with a benchmark problem.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Number of pages6
StatePublished - 2003
Externally publishedYes
Event2003 American Control Conference - Denver, CO, United States
Duration: Jun 4 2003Jun 6 2003


Other2003 American Control Conference
Country/TerritoryUnited States
CityDenver, CO

ASJC Scopus subject areas

  • Control and Systems Engineering


Dive into the research topics of 'A Two-Level Model Predictive Control Formulation for Stabilization and Optimization'. Together they form a unique fingerprint.

Cite this