Uncertainty Quantification in Control Problems for Flocking Models

Albi Giacomo; Pareschi Lorenzo; Zanella Mattia

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Uncertainty Quantification in Control Problems for Flocking Models

机译：植绒模型控制问题的不确定性量化

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The optimal control of flocking models with random inputs is investigated froma 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.

机译：从数值的角度研究了具有随机输入的植绒模型的最优控制。使用广义多项式混沌（gPC）方法，针对Cucker-Smale类型模型研究了交互参数不确定性的影响。给出了由于随机参数导致的对准动态中阈值效应的数值证据。选择性模型预测控制的使用即使在不稳定的情况下也可以使系统转向所需的状态。

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《Mathematical Problems in Engineering》 |2015年第10期|850124.1-850124.14|共14页
作者
Albi Giacomo; Pareschi Lorenzo; Zanella Mattia;
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Tech Univ Munich, Fak Math, D-85748 Munich, Germany.;

Univ Ferrara, Dept Math & Comp Sci, I-44121 Ferrara, Italy.;

Univ Ferrara, Dept Math & Comp Sci, I-44121 Ferrara, Italy.;

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Uncertainty Quantification in Control Problems for Flocking Models

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