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.

Uncertainty Quantification in Control Problems for Flocking Models

PARESCHI, Lorenzo;ZANELLA, Mattia
2015

Abstract

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.
2015
Albi, Giacomo; Pareschi, Lorenzo; Zanella, Mattia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2356384
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