From the 2 of 4 linked papers with an AI index.
4 papers
Non-asymptotic Bounds of Learning-based Linear MPC With Input Constraints and Unbounded Stochastic Noise
Changyi Lei, Seth Siriya, Dragan NeÅ¡iÄ +1
The paper proposes a certainty‑equivalence, switching model predictive control scheme that learns unknown linear dynamics online via regularized least‑squares, handling hard input…
Learning-based Homothetic Tube MPC with Non-Asymptotic Guarantees
Changyi Lei, Seth Siriya, Dragan NeÅ¡iÄ +1
The paper proposes a model predictive control method that builds a confidence set for unknown linear system parameters using regularized least‑squares, and incorporates this set in…
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…
A Framework for Adaptive Stabilisation of Nonlinear Stochastic Systems
Seth Siriya, Jingge Zhu, Dragan NeÅ¡iÄ +1
We consider the adaptive control problem for discrete-time, nonlinear stochastic systems with linearly parameterised uncertainty. Assuming access to a parameterised family of contr…