25 citations · 32 across the 6 of their papers we have counts for
7 papers · 1 filter
Statistically Consistent Inverse Optimal Control for Linear-Quadratic Tracking with Random Time Horizon
Han Zhang, Axel Ringh, Weihan Jiang +2
The goal of Inverse Optimal Control (IOC) is to identify the underlying objective function based on observed optimal trajectories. It provides a powerful framework to model expert'…
Scalable computation of dynamic flow problems via multi-marginal graph-structured optimal transport
Isabel Haasler, Axel Ringh, Yongxin Chen +1
In this work, we develop a new framework for dynamic network flow problems based on optimal transport theory. We show that the dynamic multi-commodity minimum-cost network flow pro…
On analytic interpolation with non-classical constraints for solving problems in robust control
Axel Ringh, Johan Karlsson, Anders Lindquist
In this work we consider robust stabilization of uncertain dynamical systems and show that this can be achieved by solving a non-classically constrained analytic interpolation prob…
Multi-marginal Optimal Transport with a Tree-structured cost and the Schrödinger Bridge Problem
Isabel Haasler, Axel Ringh, Yongxin Chen +1
The optimal transport problem has recently developed into a powerful framework for various applications in estimation and control. Many of the recent advances in the theory and app…
Data-driven nonsmooth optimization
Sebastian Banert, Axel Ringh, Jonas Adler +2
In this work, we consider methods for solving large-scale optimization problems with a possibly nonsmooth objective function. The key idea is to first specify a class of optimizati…
Modeling collective behaviors: A moment-based approach
Silun Zhang, Axel Ringh, Xiaoming Hu +1
In this work we introduce an approach for modeling and analyzing collective behavior of a group of agents using moments. We represent the group of agents via their distribution and…