Hybrid system identification via sparse polynomial optimization

Chao Feng, Constantino Manuel Lagoa, Mario Sznaier

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

31 Scopus citations


In this paper, the problem of identifying discrete time affine hybrid systems with measurement noise is considered. Given a finite collection of measurements and a bound on the noise, the objective is to identify a hybrid system with the smallest number of sub-systems that is compatible with the a priori information. While this problem has been addressed in the literature if the input/output data is noise-free or corrupted by process noise, it remains open for the case of measurement noise. To handle this case, we propose a new approach based on recasting the problem into a polynomial optimization form and exploiting its inherent sparse structure to obtain computationally tractable problems. Combining these ideas with a randomized Hit and Run type approach leads to further computational complexity reduction, allowing for solving realistically sized problems. Numerical examples are provided, illustrating the effectiveness of the algorithm and its potential to handle large size problems.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Number of pages6
StatePublished - 2010
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: Jun 30 2010Jul 2 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010


Other2010 American Control Conference, ACC 2010
Country/TerritoryUnited States
CityBaltimore, MD

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering


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