5 citations · 7 across the 9 of their papers we have counts for
11 papers
Over-Approximating Minimizer Sets of Constrained Convex Programs with Parametric Uncertainty via Reachability Analysis
Brendan Gould, Chih-Yuan Chiu, Antoine P. Leeman +3
We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximati…
VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis
Antoine P. Leeman, Shuyu Zhan, Melanie N. Zeilinger +1
We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction guarantees under calibrated unce…
Safety Beyond the Training Data: Robust Out-of-Distribution MPC via Conformalized System Level Synthesis
Anutam Srinivasan, Antoine Leeman, Glen Chou
We present a novel framework for robust out-of-distribution planning and control using conformal prediction (CP) and system level synthesis (SLS), addressing the challenge of ensur…
Guaranteed Robust Nonlinear MPC via Disturbance Feedback
Antoine P. Leeman, Johannes Köhler, Melanie N. Zeilinger
Robots must satisfy safety-critical state and input constraints despite disturbances and model mismatch. We introduce a robust model predictive control (RMPC) formulation that is f…
Robustly Constrained Dynamic Games for Uncertain Nonlinear Dynamics
Shuyu Zhan, Chih-Yuan Chiu, Antoine P. Leeman +1
We propose a novel framework for robust dynamic games with nonlinear dynamics corrupted by state-dependent additive noise, and nonlinear agent-specific and shared constraints. Leve…
Convex Constrained Controller Synthesis for Evolution Equations
Lauren Conger, Antoine P. Leeman, Franca Hoffmann
We propose a convex controller synthesis framework for a large class of constrained linear systems, including those described by (deterministic and stochastic) partial differential…
Fast System Level Synthesis: Robust Model Predictive Control using Riccati Recursions
Antoine P. Leeman, Johannes Köhler, Florian Messerer +3
System level synthesis enables improved robust MPC formulations by allowing for joint optimization of the nominal trajectory and controller. This paper introduces a tailored algori…
Robust Optimal Control for Nonlinear Systems with Parametric Uncertainties via System Level Synthesis
Antoine P. Leeman, Jerome Sieber, Samir Bennani +1
This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The p…
Robust Nonlinear Optimal Control via System Level Synthesis
Antoine P. Leeman, Johannes Köhler, Andrea Zanelli +2
This paper addresses the problem of finite horizon constrained robust optimal control for nonlinear systems subject to norm-bounded disturbances. To this end, the underlying uncert…
Predictive safety filter using system level synthesis
Antoine P. Leeman, Johannes Köhler, Samir Benanni +1
Safety filters provide modular techniques to augment potentially unsafe control inputs (e.g. from learning-based controllers or humans) with safety guarantees in the form of constr…
Asynchronous Computation of Tube-based Model Predictive Control
Jerome Sieber, Andrea Zanelli, Antoine P. Leeman +2
Tube-based model predictive control (MPC) methods bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. While techniques that…