Embedded learning and optimization for the next generation of smart industrial control systems

Risultati finali

Algorithm prototype implementations

Report om algorithm prototype implementations

2nd technical report on algorithms

2nd technical report on algorithms hierarchical multiscale methods for embedded MPC

2nd Dissemination and public engagement strategy repor

2nd Dissemination and public engagement strategy report

Midterm report on dissemination & communication

Midterm report on dissemination communication

1st technical report on algorithms

1st technical report on algorithms optimization algorithms for nonconvex problems and convergence analysis

Online training inventory

Online inventory for training material

1st technical report on applications

1st technical report on applications modeling of partner applications

1st technical report on implementations

1st technical report on implementations summary and analysis of requirements for learningbased MPC on embedded devices

1st Dissemination and public engagement strategy repor

1st Dissemination and public engagement strategy report

Initial network publlic web-page

Initial ELO-X public web-page

1st ELO-X seasonal school

1st ELO-X seasonal school in Leuven

2nd ELO-X seasonal school

2nd ELO-X seasonal school in Freiburg

1st ELO-X workshop

1st ELO-X workshop in Leuven

Series of ELO-X webinars

Pubblicazioni

On Recurrent Neural Networks for learning-based control: recent results and ideas for future developments

Autori: Fabio Bonassi; Marcello Farina; Jing Xie; Riccardo Scattolini
Pubblicato in: Journal of Process Control, Numero vol. 114, 2022, Pagina/e 92-104, ISSN 0959-1524
Editore: Butterworth Scientific Ltd.
DOI: 10.48550/arxiv.2111.13557

Douglas-Rachford splitting and ADMM for nonconvex optimization: accelerated and Newton-type linesearch algorithms

Autori: Andreas Themelis; Lorenzo Stella; Panagiotis Patrinos
Pubblicato in: Computational Optimization and Applications, Numero 82-2, 2022, ISSN 0926-6003
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10589-022-00366-y

Sim2real for Autonomous Vehicle Control using Executable Digital Twin

Autori: Jean Pierre Allamaa, Panagiotis Patrinos, Herman Van der Auweraer, Tong Duy Son
Pubblicato in: IFAC-PapersOnLine, Numero vol. 55 issue 24, 2022, ISSN 2405-8963
Editore: Elsevier Ltd
DOI: 10.1016/j.ifacol.2022.10.314

Data-briven Distributionally Robust Me for constrained stochastic systems

Autori: Peter Coppens; Panagiotis Patrinos
Pubblicato in: IEEE Control System Letters, Numero vol. 6, 2022, ISSN 2475-1456
Editore: IEEE
DOI: 10.1109/lcsys.2021.3091628

QPALM: a proximal augmented lagrangian method for nonconvex quadratic programs

Autori: Ben Hermans, Andreas Themelis, Panagiotis Patrinos
Pubblicato in: Mathematical Programming Computation volume, Numero 14, 2022, ISSN 1867-2949
Editore: Springer Verlag
DOI: 10.1007/s12532-022-00218-0

Large-eddy simulation of airborne wind energy farms

Autori: Thomas Haas; Jochem De Schutter; Moritz Diehl; Johan Meyers
Pubblicato in: Wind Energy Science Discussions, Numero 2, 2021, ISSN 2366-7451
Editore: Copernicus Publications
DOI: 10.5194/wes-2021-141

Recurrent Neural Network-based Internal Model Control design for stable nonlinear systems

Autori: Riccardo Scattolini; Fabio Bonassi
Pubblicato in: European Journal of Control, Numero vol. 65, 2022, ISSN 0947-3580
Editore: Lavoisier
DOI: 10.1016/j.ejcon.2022.100632

Multitrajectory Model Predictive Control for Safe UAV Navigation in an Unknown Environment

Autori: Danilo Saccani, Leonardo Cecchin, Lorenzo Fagiano
Pubblicato in: IEEE Transactions on Control Systems Technology, 2022, ISSN 1063-6536
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tcst.2022.3216989

ALPAQA: A matrix-free solver for nonlinear MPC and large-scale nonconvex optimization

Autori: Pieter Pas, Mathijs Schuurmans, Panagiotis Patrinos
Pubblicato in: 2022 European Control Conference (ECC), 2022
Editore: IEEE
DOI: 10.23919/ecc55457.2022.9838172

Introducing the quadratically-constrained quadratic programming framework in HPIPM

Autori: Frison, Gianluca; Frey, Jonathan; Messerer, Florian; Zanelli, Andrea; Diehl, Moritz
Pubblicato in: 2022 European Control Conference (ECC), 2022, Pagina/e 447-453
Editore: IEEE
DOI: 10.23919/ecc55457.2022.9838499

Towards lifelong learning of Recurrent Neural Networks for control design

Autori: Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini
Pubblicato in: 2022 European Control Conference (ECC), 2022, Pagina/e 2018-2023
Editore: IEEE
DOI: 10.23919/ecc55457.2022.9838393

An Offset-Free Nonlinear MPC scheme for systems learned by Neural NARX models

Autori: Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini
Pubblicato in: 2022 IEEE 61st Conference on Decision and Control (CDC), 2022, ISBN 978-1-6654-6761-2
Editore: IEEE
DOI: 10.1109/cdc51059.2022.9992362

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems

Autori: Thomas Pethick, Puya Latafat, Panagiotis Patrinos, Olivier Fercoq, Volkan Cevher
Pubblicato in: International Conference on Learning Representations., 2022
Editore: ICLR

An Inverse Optimal Control Approach for Trajectory Prediction of Autonomous Race Cars

Autori: Rudolf Reiter, Florian Messerer, Markus Schratter, Daniel Watzenig, Moritz Diehl
Pubblicato in: 2022 European Control Conference (ECC), 2022
Editore: IEEE
DOI: 10.23919/ecc55457.2022.9838100

Risultati finali

Pubblicazioni

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