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eess.SY2026
Non-asymptotic Bounds of Learning-based Linear MPC With Input Constraints and Unbounded Stochastic Noise
Changyi Lei, Seth Siriya, Dragan Nešić +1
This paper studies learning-based model predictive control (MPC) for stabilizing unknown discrete-time linear systems with hard input constraints and additive unbounded sub-Gaussia…
eess.SY2026
Learning-based Homothetic Tube MPC with Non-Asymptotic Guarantees
Changyi Lei, Seth Siriya, Dragan Nešić +1
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 t…
math.OC2026
A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
Yujia Luo, Ye Pu, Jonathan H. Manton +1
This paper presents a PAC-Bayes framework for learning controllers for unknown stochastic linear discrete-time systems, where the system parameters are drawn from a fixed but unkno…