Bart De Schutter

Research interests

Publications

• Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

  arXiv (Cornell University) · 2020 · 10.1016/j.apenergy.2021.116983

• Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms

  Applied Energy · 2018 · https://doi.org/10.1016/j.apenergy.2018.02.069

• Forecasting day-ahead electricity prices in Europe: The importance of considering market integration

  Applied Energy · 2017 · 10.1016/j.apenergy.2017.11.098

• Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning

  IEEE Transactions on Smart Grid · 2016 · 10.1109/tsg.2016.2517211

• Deep convolutional neural networks for detection of rail surface defects

  · 2016 · 10.1109/ijcnn.2016.7727522

• Passenger-demands-oriented train scheduling for an urban rail transit network

  Transportation Research Part C Emerging Technologies · 2015 · 10.1016/j.trc.2015.07.012

• Optimal trajectory planning for trains – A pseudospectral method and a mixed integer linear programming approach

  Transportation Research Part C Emerging Technologies · 2013 · 10.1016/j.trc.2013.01.007

• Accelerated gradient methods and dual decomposition in distributed model predictive control

  Automatica · 2013 · 10.1016/j.automatica.2013.01.009

• Efficient network-wide model-based predictive control for urban traffic networks

  Transportation Research Part C Emerging Technologies · 2012 · 10.1016/j.trc.2012.02.003

• A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark

  Journal of Process Control · 2011 · 10.1016/j.jprocont.2011.03.003

• Fast Model Predictive Control for Urban Road Networks via MILP

  IEEE Transactions on Intelligent Transportation Systems · 2011 · 10.1109/tits.2011.2114652

• Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models

  Studies in fuzziness and soft computing · 2010 · 10.1007/978-3-642-16776-8

• Reinforcement Learning and Dynamic Programming Using Function Approximators

  Journal · 2010 · https://doi.org/10.1201/9781439821091

• Demand Response With Micro-CHP Systems

  Proceedings of the IEEE · 2010 · 10.1109/jproc.2010.2053831

• Multi-agent Reinforcement Learning: An Overview

  Studies in computational intelligence · 2010 · https://doi.org/10.1007/978-3-642-14435-6_7

• Distributed model predictive control of irrigation canals

  Networks and Heterogeneous Media · 2009 · 10.3934/nhm.2009.4.359

• A Comprehensive Survey of Multiagent Reinforcement Learning

  IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · 2008 · https://doi.org/10.1109/tsmcc.2007.913919

• Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

  Engineering Applications of Artificial Intelligence · 2007 · 10.1016/j.engappai.2007.08.005

• Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations

  Vehicle System Dynamics · 2006 · 10.1080/00423110600563338

• Model predictive control for optimal coordination of ramp metering and variable speed limits

  Transportation Research Part C Emerging Technologies · 2005 · 10.1016/j.trc.2004.08.001

• Model predictive control for ramp metering of motorway traffic: A case study

  Control Engineering Practice · 2005 · 10.1016/j.conengprac.2005.03.010

• Robust output-feedback controller design via local BMI optimization

  Automatica · 2004 · 10.1016/j.automatica.2004.01.028

• Model predictive control for max-plus-linear discrete event systems

  Automatica · 2001 · 10.1016/s0005-1098(01)00054-1

• Equivalence of hybrid dynamical models

  Automatica · 2001 · https://doi.org/10.1016/s0005-1098(01)00059-0

• DAISY : A database for identification of systems

  Journal A · 1997

Current projects

No projects listed.