Stochastic MPC with robustness to bounded parameteric uncertainty

E Arcari, A Iannelli, A Carron… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
In this article, we present a stochastic model predictive control approach for discrete-time LTI
systems subject to bounded parameteric uncertainty and potentially unbounded stochastic …

Learning the uncertainty sets of linear control systems via set membership: A non-asymptotic analysis

Y Li, J Yu, L Conger, T Kargin… - Forty-first International …, 2024‏ - openreview.net
This paper studies uncertainty set estimation for unknown linear systems. Uncertainty sets
are crucial for the quality of robust control since they directly influence the conservativeness …

An explicit dual control approach for constrained reference tracking of uncertain linear systems

A Parsi, A Iannelli, RS Smith - IEEE Transactions on Automatic …, 2022‏ - ieeexplore.ieee.org
A finite horizon optimal tracking problem is considered for linear dynamical systems subject
to parametric uncertainties in the state-space matrices and exogenous disturbances. A …

Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties

X Ma, S Zhang, Y Li, F Qian, Z Sun… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
This article is concerned with the robust tracking control of linear uncertain systems, whose
unknown system parameters and disturbances are bounded within ellipsoidal sets. We …

Learning the uncertainty sets for control dynamics via set membership: A non-asymptotic analysis

Y Li, J Yu, L Conger, T Kargin, A Wierman - arxiv preprint arxiv …, 2023‏ - arxiv.org
This paper studies uncertainty set estimation for unknown linear systems. Uncertainty sets
are crucial for the quality of robust control since they directly influence the conservativeness …

Safe navigation in unstructured environments by minimizing uncertainty in control and perception

J Seo, J Mun, T Kim - arxiv preprint arxiv:2306.14601, 2023‏ - arxiv.org
Uncertainty in control and perception poses challenges for autonomous vehicle navigation
in unstructured environments, leading to navigation failures and potential vehicle damage …

On the convergence rates of set membership estimation of linear systems with disturbances bounded by general convex sets

H Xu, Y Li - arxiv preprint arxiv:2406.00574, 2024‏ - arxiv.org
This paper studies the uncertainty set estimation of system parameters of linear dynamical
systems with bounded disturbances, which is motivated by robust (adaptive) constrained …

Robust MPC for linear systems with parametric and additive uncertainty: A novel constraint tightening approach

M Bujarbaruah, U Rosolia, YR Stürz, X Zhang… - arxiv preprint arxiv …, 2020‏ - arxiv.org
We propose a novel approach to design a robust Model Predictive Controller (MPC) for
constrained uncertain linear systems. The uncertain system is modeled as linear parameter …

A distributed framework for linear adaptive MPC

A Parsi, A Aboudonia, A Iannelli… - 2021 60th IEEE …, 2021‏ - ieeexplore.ieee.org
Adaptive model predictive control (MPC) robustly ensures safety while reducing uncertainty
during operation. In this paper, a distributed version is proposed to deal with network …

[ספר][B] Safe and Scalable Learning-Based Control: Theory and Application in Sustainable Energy Systems

J Yu - 2025‏ - search.proquest.com
From intelligent transportation systems to the smart grid, the next generation of cyber-
physical systems (CPS) will substantially transform our society. It is vital that these systems …