Organization profile

Introduction / mission

The research field of CS is the area of dynamic modelling and model-based control of complex dynamic systems.

Highlighted phrase

Enabling smart, high-performance operation of technical systems across technology domains

Organisational profile

The mission of the group is to be an internationally recognized centre of research in systems and control, where contributions to fundamental theory are combined with advancing innovative technological applications in a selected number of domains, in cooperation with relevant industrial partners. The fundamental research of CS is directed towards the following research lines:

• Data-driven modelling in dynamic networks
• Modelling and control of linear parameter varying systems
• Spatial-temporal multi-physics systems and model reduction
• Data analytics and machine learning
• Constrained and interconnected systems
• Model-based control and optimization
• Control of cyber-physical systems

Application domains range from multi-physics high-tech/mechatronic systems, automotive systems, energy and power converter systems to industrial process control systems. In each of these domains CS collaborates with leading companies contributing our fundamental knowledge to their innovation roadmaps.

CS actively participates in the research program of the national research school DISC (Dutch Institute of Systems and Control) and significantly contributes to the “Smart and Sustainable Systems” program of the EE department. Cooperative links exist with the EE groups EPE and EES and the ME groups CST and DC.

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Controllers Engineering & Materials Science

Identification (control systems) Engineering & Materials Science

Model predictive control Engineering & Materials Science

Lyapunov functions Engineering & Materials Science

Scheduling Engineering & Materials Science

Nonlinear systems Engineering & Materials Science

Linear systems Engineering & Materials Science

Energy management Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Profiles

Alrianes A. Bachnas, MSc

a.a.bachnas@tue.nl

Department of Electrical Engineering, Control Systems - Former Doctoral Candidate

Person: Unknown

A.C.P.M. (Ton) Backx

a.c.p.m.backx@tue.nl

Institute for Photonic Integration - Full Professor
Department of Electrical Engineering, Control Systems - Full Professor

Person: HGL : Professor

Henrik Beelen

h.p.g.j.beelen@tue.nl

Department of Electrical Engineering, Dynamics and Control for Electrified Automotive Systems
Department of Electrical Engineering, Control Systems - Former Doctoral Candidate

Person: Prom. : doctoral candidate (PhD), Unknown

Research Output 1968 2020

An advanced all-solid-state Li-ion battery model

Raijmakers, L. H. J., Danilov, D. L., Eichel, R. A. & Notten, P. H. L., 10 Jan 2020, In : Electrochimica Acta. 330, 19 p., 135147.

Research output: Contribution to journal › Article › Academic › peer-review

Electrolytes

Electrodes

Electric space charge

Lithium

Charge transfer

Heterogeneously parameterized tube model predictive control for LPV systems

Hanema, J., Lazar, M. & Tóth, R., 1 Jan 2020, In : Automatica. 111, 13 p., 108622.

Research output: Contribution to journal › Article › Academic › peer-review

Model predictive control

Parameterization

Costs

Achievements in correct-by-design control for stochastic systems

Haesaert, S. & Soudjani, S., 15 Apr 2019, SNR 2019 - Proceedings of the 5th International Workshop on Symbolic-Numeric Methods for Reasoning about CPS and IoT. Ramachandran, G. S. & Ortiz, J. (eds.). New York: Association for Computing Machinery, Inc, 4 p. 3313368

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Stochastic systems

Control Design

Stochastic Systems

Synthesis

Controller