Design of nonlinear MPC by Kriging-based optimization

Julien Marzat (1) , Hélène Piet-Lahanier (1)

1 ONERA - The French Aerospace Lab [Palaiseau]

This paper investigates the on-line design of nonlinear model predictive control by the use of Kriging as a surrogate model for optimization. This representation is able to address various optimization problems at a very reduced computational cost. It is thus advocated here to deal with nonlinear models in the context of NMPC. One of the main objectives is to assess whether this strategy may be processed in real-time, while ensuring accurate control. An application to the guidance law design of an unmanned aerial vehicle is reported to illustrate the resulting performance.

Mots clés: efficient global optimization; Gaussian process; optimal guidance; Kriging; nonlinear model predictive control; unmanned aerial vehicle

Domaines: Automatique / Robotique

Julien Marzat, Hélène Piet-Lahanier. Design of nonlinear MPC by Kriging-based optimization. 16th IFAC Symposium on System Identification, Jul 2012, Bruxelles, Belgium. pp.1490-1495. ⟨hal-00680766⟩