Uncertainty Quantification in Control Problems for Flocking Models

Giacomo Albi, Lorenzo Pareschi, Mattia Zanella

Mathematical Problems in Engineering, Vol. 2015. Open Access. Preprint arXiv.

In this paper the optimal control of flocking models with random inputs is investigated from a numerical point of view. The effect of uncertainty in the interaction parameters is studied for a Cucker-Smale type model using a generalized polynomial chaos (gPC) approach. Numerical evidence of threshold effects in the alignment dynamic due to the random parameters is given. The use of a selective model predictive control permits to steer the system towards the desired state even in unstable regimes.