Uncertainty Quantification in Control Problems for Flocking Models

2015/03/02 by Albi, Giacomo, Pareschi, Lorenzo, Zanella, Mattia
#Adaptation and Self-Organizing Systems (nlin.AO) #FOS: Mathematics #FOS: Physical sciences #Numerical Analysis (math.NA) #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.1503.00548

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.

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