@inproceedings{a81e7e70a97f4ed9adb0652604cc0db5,
title = "Data-driven modelling, learning and stochastic predictive control for the steel industry",
keywords = "air pollution control, combustion, energy consumption, furnaces, heating, learning systems, predictive control, steel industry, stochastic processes, learning control, stochastic predictive control, data-driven modelling, energy-intensive processes, controlled process, online modelling, uncertainty-aware predictive control, risk-sensitive model selection, risk measures, dynamical models, process data, walking beam furnace, Swerea MEFOS, scenario-based model predictive controller, temperature references, heating zones, classifier training, oxygen, thermal efficiency, Furnaces, Predictive models, Heating systems, Combustion, Legged locomotion, Computational modeling, Process control, Advanced Process Control, Machine Learning, Stochastic Model Predictive Control, Risk-sensitive Model Selection, Cyber-Physical Systems",
author = "D. Herceg and G. Georgoulas and P. Sopasakis and M. Casta{\~n}o and P. Patrinos and A. Bemporad and J. Niemi and G. Nikolakopoulos",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/MED.2017.7984308",
language = "Undefined/Unknown",
pages = "1361--1366",
booktitle = "2017 25th Mediterranean Conference on Control and Automation (MED)",
}