Advanced nonlinear model predictive control: Theory, numerical aspects, and applications

The research activity is aimed in investigating the theoretical and, numerical, and application aspects concerning the Nonlinear Model Predictive Control (NMPC). In particular, the theoretical aspects will focus on:

  • Optimization by means of the Pontryagin Minimum Principle.
  • Constrained solution through penalty function methodology.
  • Nonlinear finite-time stability.
  • Robust NMPC design and stability.
  • System controllability in presence of input and state constraints.

Moreover, the numerical aspects of the NMPC solutions are studied, in order to enhance the algorithm flexibility and implementability, with hardware-in-the-loop, in real-time control applications.
The theoretical/methodological results are, then, tested and confirmed by simulation, with a focus on automotive and aerospace mechatronics systems.

Erc Sector:

  • PE7_1 Control engineering
  • PE7_3 Simulation engineering and modelling


  • Predictive Control
  • Nonlinear control systems 

Research groups