5 citations · 7 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
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 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…