Errors-in-Variables Data-Driven Receding-Horizon LQR
This letter addresses the data-driven linear quadratic regulator (LQR) problem with input constraints under process noise and errors-in-variables measurement errors. Using noisy state and input measurements, we design controllers that ensure closed-loop stability, minimize a quadratic cost, and respect input bounds wit...