A co-processor FPGA platform for the implementation of real-time model predictive control

Leonidas G. Bleris, Panagiotis D. Vouzis, Mark G. Arnold, Mayuresh V. Kothare

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

54 Scopus citations


In order to effectively control nonlinear and multivariable models, and to incorporate constraints on system states, inputs and outputs (bounds, rate of change), a suitable (sometimes necessary) controller is Model Predictive Control (MPC). MPC is an optimization-based control scheme that requires abundant matrix operations for the calculation of the optimal control moves. In this work we propose a mixed software and hardware embedded MPC implementation. Using a codesign step and based on profiling results, we decompose the optimization algorithm into two parts: one that fits into a host processor and one that fits into a custom made unit, that performs the computationally demanding arithmetic operations. The profiling results and information on the co-processor design are provided.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Number of pages6
StatePublished - 2006
Externally publishedYes
Event2006 American Control Conference - Minneapolis, MN, United States
Duration: Jun 14 2006Jun 16 2006


Other2006 American Control Conference
Country/TerritoryUnited States
CityMinneapolis, MN

ASJC Scopus subject areas

  • Control and Systems Engineering


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