3 papers indexed
Changyi Lei, Seth Siriya, Dragan Nešić, Ye Pu
This paper studies learning-based model predictive control (MPC) for stabilizing unknown discrete-time linear systems with hard input constraints and additive unbounded sub-Gaussian disturbances. We adopt a certainty-equivalence (CE) design that combines a switching MPC control l…
Changyi Lei, Seth Siriya, Dragan Nešić, Ye Pu
This paper studies learning-based MPC for constrained stabilization of discrete-time linear systems with unknown system parameters and additive bounded disturbances. We develop a tractable homothetic-tube MPC scheme in which a high-probability parameter confidence set is generate…
Robert H. Moldenhauer, Dragan Nešić, Mathieu Granzotto, Romain Postoyan, Andrew R. Teel
We study conditions under which stability of the origin of stochastic differential equations is robust to small perturbations. We express robustness in two ways, firstly in the sense that stochastic stability is maintained under small parametric perturbations not exceeding a stat…