Uncertainty Quantification in Control Problems for Flocking Models


Giacomo Albi, Lorenzo Pareschi, Mattia Zanella 
(5/3/2015 Math. Probl. Eng.  (2015), Art. ID 850124, 14 pp.,  arXiv:1503.00548)

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.

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