Uncertainty Quantification in Control Problems for Flocking Models

Giacomo Albi, Lorenzo Pareschi and Mattia Zanella

Mathematical Problems in Engineering, 2015, vol. 2015, 1-14

Abstract:

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 steering of the system towards the desired state even in unstable regimes.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:850124

DOI: 10.1155/2015/850124

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