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Fakultät für Elektrotechnik und Informationstechnik

Optimization-based control, which includes optimal control and model predictive control, is a very active field of research which has seen tremendous progress in terms of analysis and tools for implementation.

“Predictive Control, or Model-Based Predictive Control [...] as it is sometimes known, is the only advanced control technique – that is, more advanced than standard PID control – to have had a significant and widespread impact on industrial process control.” 
— Jan Maciejowski, “Predictive Control – With Constraints”, Pearson Education, 2002

In this context, we work on

  • Stability analysis and design methods for MPC
  • Tools and numerical methods for implementation
  • Economic MPC and MPC for uncertain systems

We also offer a research-oriented course on Nonlinear MPC to Master's students.

Selected Publications:

  • Faulwasser, T., Grüne, L., & Müller, M. A. (2018). Economic nonlinear model predictive control. Foundations and Trends® in Systems and Control, 5(1), 1-98.
  • Faulwasser, T., Korda, M., Jones, C. N., & Bonvin, D. (2017). On turnpike and dissipativity properties of continuous-time optimal control problems. Automatica, 81, 297-304.
  • Zanon, M., & Faulwasser, T. (2018). Economic MPC without terminal constraints: Gradient-correcting end penalties enforce asymptotic stability. Journal of Process Control, 63, 1-14.
  • Faulwasser, T., & Findeisen, R. (2015). Nonlinear model predictive control for constrained output path following. IEEE Transactions on Automatic Control61(4), 1026-1039.