Development of online solution algorithms for optimal periodic control problems with plant uncertainties

Mohammad Ghanaatpishe, Michelle Kehs, Hosam K. Fathy

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

3 Scopus citations


This paper introduces two online methods for optimal periodic control (OPC) of open-loop stable plants. The first method requires knowledge of the plant structure but allows for uncertainty in plant parameters. It employs recursive least squares to estimate parameters, then uses the estimates to adapt the shape of the optimal trajectory. The second method uses a model-free extremum seeking scheme to slowly converge to the optimal input trajectory. While relevant work has been done in the area of online optimal periodic control, the existing methods either rely heavily on knowledge of the plant or they assume a known period. This work proposes methods that do not require these assumptions/limitations. The methods are tested on a drug delivery example from the existing OPC literature. Average drug efficacy values obtained in this work are comparable to the literature, even though limited information about the plant is used.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781479986842
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Publication series

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


Other2015 American Control Conference, ACC 2015
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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