2019 - IEEE Fellow For contributions to optimal control of discrete-event and hybrid systems
His primary areas of investigation include Model predictive control, Mathematical optimization, Control theory, Optimal control and Nonlinear system. His research in Model predictive control intersects with topics in Control engineering, Cogeneration, Speed limit and Traffic flow. His work in Mathematical optimization addresses subjects such as Nonlinear programming, which are connected to disciplines such as Integer programming.
His work on Control theory, Lyapunov function, Linear system and State variable as part of general Control theory study is frequently connected to Scale, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Optimal control research is multidisciplinary, incorporating perspectives in Routing, Aggregate, Grid network and Road traffic control. Bart De Schutter interconnects Operations research, Numerical linear algebra and Sequential quadratic programming in the investigation of issues within Nonlinear system.
Bart De Schutter focuses on Mathematical optimization, Model predictive control, Control theory, Control and Optimization problem. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Function, Computation and Computational complexity theory. The concepts of his Model predictive control study are interwoven with issues in Traffic flow, Reduction, Control engineering, Control theory and Simulation.
His Control theory study frequently links to adjacent areas such as Bounded function. His Control research includes themes of Routing and Transport engineering. His Linear system study frequently links to related topics such as Algorithm.
His main research concerns Mathematical optimization, Control theory, Model predictive control, Optimization problem and Control. His Mathematical optimization research integrates issues from Distributed generation, State and Benchmark. He combines subjects such as Bottleneck and Speed limit with his study of Control theory.
His work carried out in the field of Model predictive control brings together such families of science as Probabilistic logic, Microgrid and Optimal control. His work deals with themes such as Function and Distributed algorithm, which intersect with Optimization problem. His Control study combines topics in areas such as Control system and Reduction.
Bart De Schutter spends much of his time researching Model predictive control, Control theory, Mathematical optimization, Optimization problem and Linear programming. Model predictive control is a subfield of Control that he explores. His Control theory research is multidisciplinary, relying on both Bottleneck, Speed limit, Control algorithm and Bounded function.
His research integrates issues of Phasor, Control theory, Probabilistic logic and State in his study of Mathematical optimization. He studied Linear programming and Nonlinear programming that intersect with Regenerative brake. The concepts of his Linear system study are interwoven with issues in Concurrency and Algebra.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Reinforcement Learning and Dynamic Programming Using Function Approximators
Lucian Busoniu;Robert Babuska;Bart De Schutter;Damien Ernst.
Model predictive control for optimal coordination of ramp metering and variable speed limits
Andreas Hegyi;Bart De Schutter;Hans Hellendoorn.
Transportation Research Part C-emerging Technologies (2005)
Optimal coordination of variable speed limits to suppress shock waves
A. Hegyi;Bart De Schutter;J. Hellendoorn.
IEEE Transactions on Intelligent Transportation Systems (2005)
Brief Model predictive control for max-plus-linear discrete event systems
Bart De Schutter;Ton Van Den Boom.
Multi-agent Reinforcement Learning: An Overview
Lucian Buşoniu;Robert Babuška;Bart De Schutter.
DAISY : A database for identification of systems
Bart De Moor;P De Gersem;Bart De Schutter;W Favoreel.
Journal A (1997)
Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models
Robert Babuska;Bart De Schutter;Zsfia Lendek;T. M. Guerra.
Demand Response With Micro-CHP Systems
Michiel Houwing;Rudy R Negenborn;Bart De Schutter.
Proceedings of the IEEE (2011)
Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms
Jesus Lago;Fjo De Ridder;Bart De Schutter.
Applied Energy (2018)
Distributed model predictive control of irrigation canals
Rudy R. Negenborn;Peter-Jules van Overloop;Tamás Keviczky;Bart De Schutter.
Networks and Heterogeneous Media (2009)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: