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Data-driven Linear Quadratic Regulation via Semidefinite Programming

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arxiv 1911.07767 v2 pith:REZOOIRU submitted 2019-11-18 eess.SY cs.SYmath.OC

Monica Rotulo , Claudio De Persis , Pietro Tesi This is my paper · ORCID
classification eess.SYcs.SYmath.OC
keywords systemdatalinearquadraticregulationsemidefiniteaccessibleapproach
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This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state is accessible. Information on the system is given by a finite set of input-state data, where the input injected in the system is persistently exciting of a sufficiently high order. Using data, the optimal control law is then obtained as the solution of a suitable semidefinite program. The effectiveness of the approach is illustrated via numerical examples.

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