SIC - System Identification & Control

The System Identification and Control group includes a full professor, two associate professors and an assistant professor, and its research activity is focused on the following topics:

  • Identification of linear, nonlinear and linear parameter varying models through Set Membership methodologies
  • Identification of block structured and nonlinear interconnected models, with particular focus on the development of algorithms for computing tight "hard" bounds on the parameters of the linear and nonlinear subsytems  
  • Convex relaxation methodologies for the approximation of the global optimal solutions to non convex optimization problems arising from specific problems in the field of Set Membership identification and robust control
  • Fast implementation of predictive control laws by approximating its representation as a static function of the system state by means of original nonlinear approximation techniques recently developed by the group.
  • Robust control in the presence of input saturation constraints, introducing new approaches in the context of Model Predictive Control and Internal Model Control frameworks.
  • Identification and control of automotive systems, with particular focus on modeling, identification and control of the longitudinal, lateral and vertical dynamics of the vehicle by means of the original methodological approaches listed above.


  • Set Membership identification and parameter estimation
  • Identification of linear, linear parameter varying, nonlinear and block structured models
  • Convex relaxation techniques for identification and control of dynamical systems
  • Robust control of uncertain systems
  • Model predictive control
  • Identification and control of automotive systems 

Projects and publications