Jul 2026
Non-asymptotic Bounds of Learning-based Linear MPC With Input Constraints and Unbounded Stochastic Noise
A certainty-equivalence design is adopted that combines a switching MPC control law with online regularized least-squares (RLS) parameter estimation, resulting in non-asymptotic, high-probability stability bounds for the closed-loop system under the proposed switching controller.
Chang-Yi Lei, Seth Siriya, D. Nešić et al.
· arXiv.org · 0 citations