Johan U. Backström

Engineering · Physical Sciences

11h-index442citations39works0.02yr avg
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Research Topics

Advanced Control Systems Optimization(29), Fault Detection and Control Systems(25), Control Systems and Identification(15), Fuel Cells and Related Materials(6), Iterative Learning Control Systems(5)

Publications39 total

Improved Resolution and Precision of whole-brain multi-parametric qMRI using Deep Learning Denoising and Super-Resolution Reconstruction
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition·2025
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems
arXiv (Cornell University)·2022Open Access
Meta-reinforcement learning for the tuning of PI controllers: An offline approach
Journal of Process Control·2022· 41 cited
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems
2022· 4 cited
Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach
arXiv (Cornell University)·2022· 3 citedOpen Access
Deep reinforcement learning with shallow controllers: An experimental application to PID tuning
Control Engineering Practice·2022· 103 citedOpen Access
Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning
arXiv (Cornell University)·2021· 3 citedOpen Access
Approximately Optimal Fixed-Structure Controllers Using Neural Networks
2021Open Access
Almost Surely Stable Deep Dynamics
arXiv (Cornell University)·2021· 8 citedOpen Access
Model-plant mismatch detection for cross-directional processes
ISA Transactions·2021· 2 cited
A Meta-Reinforcement Learning Approach to Process Control
IFAC-PapersOnLine·2021Open Access
Almost Surely Stable Deep Dynamics
Figshare·2020· 3 citedOpen Access
Support vector machine approach for model-plant mismatch detection
Computers & Chemical Engineering·2019· 13 cited
User-friendly cross-directional MPC tuning for uncertain multiple-array paper-making processes
Control Engineering Practice·2019· 16 cited
Machine Direction Adaptive Control on a Paper Machine
Industrial & Engineering Chemistry Research·2019· 5 cited
Identification of symmetric noncausal processes
Automatica·2019· 1 cited
Robust Tuning of Cross-Directional Model Predictive Controllers for Paper-Making Processes
IEEE Transactions on Control Systems Technology·2017· 5 cited
Model-Plant Mismatch Detection with Support Vector Machines
IFAC-PapersOnLine·2017· 5 citedOpen Access
Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines
2017
Robust tuning for machine-directional predictive control of MIMO paper-making processes
Control Engineering Practice·2016· 15 cited
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Frequent Co-authors

Michael G. Forbes(30), R. Bhushan Gopaluni(23), Philip D. Loewen(22), Guy A. Dumont(15), Nathan P. Lawrence(10), Qiugang Lu(9), Daniel G. McClement(8), Tongwen Chen(7), Ning He(5), Mahdi Yousefi(5), Danlei Chu(4), Dawei Shi(4), Jiadong Wang(4), Lee D. Rippon(4), Cristian Gheorghe(3), Ahmed Ismail(2), Roscoe Bartlett(1), Lorenz T. Biegler(1), Vipin Gopal(1), Stephen M. Chu(1)