Uncertainty Quantification in Control Problems for Flocking Models
Numerical Analysis
2015-03-03 v1 Optimization and Control
Adaptation and Self-Organizing Systems
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.
Cite
@article{arxiv.1503.00548,
title = {Uncertainty Quantification in Control Problems for Flocking Models},
author = {Giacomo Albi and Lorenzo Pareschi and Mattia Zanella},
journal= {arXiv preprint arXiv:1503.00548},
year = {2015}
}