SC Guide Information

The model predictive control (MPC) strategy yields the optimization of a performance index with respect to some future control sequence, using predictions of the output signal based on a process model, coping with amplitude constraints on inputs, outputs and states. The course presents an overview of the most important predictive control strategies, the theoretical aspects as well as the practical implications, that makes model predictive control so successful in many areas of industry, such as petro-chemical industry and chemical process industry. Hands-on experience is obtained by MATLAB exercises with academic examples.

Contents of the course:

  • General introduction. Differences in models and modelstructures, advantages and limitations. Prediction models in state-space setting.
  • Standard predictive control scheme. Relation standard form with GPC, LQPC and other predictive control schemes. Solution of the standard predictive control problem.
  • Stability, robustness, initial and advanced tuning. Predictive control based on Linear Matrix Inequalities.
  • Robust design in predictive control.
  • Lecturers:
    dr. ir. Ton J.J. van den Boom, room WbMT-8C.3.09, tel: 84052,

    Undergraduate curriculum, experience with MATLAB could be useful but is not required.

    Study load:
    4 ECTS / 112 hours

    Course material:
    Course notes Model Predictive Control by Ton van den Boom, Delft, December 2008 (sold by "diktatenverkoop")
    Handouts (available via the download page)