Data-Driven Reinforcement Learning Control using Model Reduction Techniques: Theory and Applications to Power Systems.

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dc.contributor.advisorAranya Chakrabortty, Chair
dc.contributor.advisorIqbal Husain, Member
dc.contributor.advisorEdgar Lobaton, Member
dc.contributor.advisorFen Wu, Member
dc.contributor.authorMukherjee, Sayak
dc.date.accepted2020-04-06
dc.date.accessioned2020-04-09T15:38:55Z
dc.date.available2020-04-09T15:38:55Z
dc.date.defense2020-03-23
dc.date.issued2020-03-23
dc.date.released2020-04-09
dc.date.reviewed2020-03-25
dc.date.submitted2020-03-24
dc.degree.disciplineElectrical Engineering
dc.degree.leveldissertation
dc.degree.nameDoctor of Philosophy
dc.identifier.otherdeg20610
dc.identifier.urihttps://www.lib.ncsu.edu/resolver/1840.20/37368
dc.titleData-Driven Reinforcement Learning Control using Model Reduction Techniques: Theory and Applications to Power Systems.

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