5 citations · 11 across the 8 of their papers we have counts for
14 papers
Learning Models of Model Predictive Controllers using Gradient Data
Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg
This paper investigates controller identification given data from a Model Predictive Controller (MPC) with constraints. We propose an approach for learning MPC that explicitly uses…
Cooperative System Identification via Correctional Learning
Inês Lourenço, Robert Mattila, Cristian R. Rojas +1
We consider a cooperative system identification scenario in which an expert agent (teacher) knows a correct, or at least a good, model of the system and aims to assist a learner-ag…
A Geometric Approach to On-road Motion Planning for Long and Multi-Body Heavy-Duty Vehicles
Rui Oliveira, Oskar Ljungqvist, Pedro F. Lima +2
Driving heavy-duty vehicles, such as buses and tractor-trailer vehicles, is a difficult task in comparison to passenger cars. Most research on motion planning for autonomous vehicl…
Learning the Step-size Policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm
Lucas N. Egidio, Anders Hansson, Bo Wahlberg
We consider the problem of how to learn a step-size policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. This is a limited computational memory quasi-…
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression
Arun Venkitaraman, Anders Hansson, Bo Wahlberg
This paper investigates the use of nonparametric kernel-regression to obtain a tasksimilarity aware meta-learning algorithm. Our hypothesis is that the use of tasksimilarity helps…
On Training and Evaluation of Neural Network Approaches for Model Predictive Control
Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg
The contribution of this paper is a framework for training and evaluation of Model Predictive Control (MPC) implemented using constrained neural networks. Recent studies have propo…