DISC field and themes

DISC field and themes

The research program of DISC consists of fundamental and applied scientific research in the domain of systems and control theory and engineering. The research domain employs modern techniques from information and computer technology to analyse, control and optimize dynamical processes, machines and (high-tech) systems. Modelling tools are essential in analysing and designing optimal control strategies, e.g. by exploiting optimization theory. Mathematical System Theory provides insight in the formulation of mathematical models, in the derivation of mathematical models from experimental data, and in the design of control and feedback signals.

The orientation towards a variety of technological application domains is important for the interplay between theoretical possibilities on the one side, and the urge to advance high-tech applications on the other side, thereby providing a fruitful stimulus for further evolution and development of the scientific area. Research groups within DISC have many interactions with adjacent scientific domains, among which

  • informatics, embedded systems (UT,TUe)
  • mechanics, mechatronics, manufacturing and robotics (TUe, TUD, UT)
  • agricultural sciences, bio- and foodtechnology (WU)
  • biomedical engineering (TUe, TUD, UT, UM)
  • physics of microsystems and optics (TUe, TUD, UT)
  • financial engineering (TU, TUD, UT)
  • optimization theory, numerical algorithms (TUD, UT,RUG)
  • information theory, stochastics (CWI, UT, TUD)
  • (petro)chemical processes (TUe, TUD)
  • systems biology (CWI,RUG-IWI)
  • automotive and transportation systems (TUe,TUD)
  • aerospace systems (TUD)

The research program of DISC

The research program of DISC is divided in three main areas, each of which contains several themes.

  • System and control theory
    • System theory, including behavioral systems, nonlinear, distributed and hybrid systems.
    • Control theory for nonlinear, robust, adaptive, optimal control.
  • Theory and application of system modelling
    • System identification, estimation and signal processing;
    • Modelling tools: discrete events, hybrid systems, fuzzy logic/neural networks;
  • Applications of control engineering
    • Mechatronics, robotics, precision technology, motion control systems;
    • Process control and optimization.