4 citations · 11 across the 9 of their papers we have counts for
9 papers
GPU-Accelerated Cholesky Factorization of Block Tridiagonal Matrices
Roland Schwan, Daniel Kuhn, Colin N. Jones
This paper presents a GPU-accelerated framework for solving block tridiagonal linear systems that arise naturally in numerous real-time applications across engineering and scientif…
Parallel KKT Solver in PIQP for Multistage Optimization
Fenglong Song, Roland Schwan, Yuwen Chen +1
This paper presents an efficient parallel Cholesky factorization and triangular solve algorithm for the Karush-Kuhn-Tucker (KKT) systems arising in multistage optimization problems…
Exploiting Multistage Optimization Structure in Proximal Solvers
Roland Schwan, Daniel Kuhn, Colin N. Jones
This paper presents an efficient structure-exploiting algorithm for multistage optimization problems. The proposed method extends existing approaches by supporting full coupling be…
Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations
Gösta Stomberg, Roland Schwan, Andrea Grillo +2
This paper presents experiments for embedded cooperative distributed model predictive control applied to a team of hovercraft floating on an air hockey table. The hovercraft collec…
On identifying the non-linear dynamics of a hovercraft using an end-to-end deep learning approach
Roland Schwan, Nicolaj Schmid, Etienne Chassaing +2
We present the identification of the non-linear dynamics of a novel hovercraft design, employing end-to-end deep learning techniques. Our experimental setup consists of a hovercraf…
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Truong X. Nghiem, Ján Drgoňa, Colin Jones +10
Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathema…
PIQP: A Proximal Interior-Point Quadratic Programming Solver
Roland Schwan, Yuning Jiang, Daniel Kuhn +1
This paper presents PIQP, a high-performance toolkit for solving generic sparse quadratic programs (QP). Combining an infeasible Interior Point Method (IPM) with the Proximal Metho…
On continuation and convex Lyapunov functions
Wouter Jongeneel, Roland Schwan
Suppose that the origin is globally asymptotically stable under a set of continuous vector fields on Euclidean space and suppose that all those vector fields come equipped with --…
Stability Verification of Neural Network Controllers using Mixed-Integer Programming
Roland Schwan, Colin N. Jones, Daniel Kuhn
We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, w…