<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In this paper the optimal control of alignment models composed by a large number of agents is investigated in presence of a selective action of a controller, acting in order to enhance consensus. Two types of selective controls have been presented: an homogeneous control filtered by a selective function and a distributed control active only on a selective set. As a first step toward a reduction of computational cost, we introduce a model predictive control (MPC) approximation by deriving a numerical scheme with a feedback selective constrained dynamics. Next, in order to cope with the numerical solution of a large number of interacting agents, we derive the mean-field limit of the feedback selective constrained dynamics, which eventually will be solved numerically by means of a stochastic algorithm, able to simulate effciently the selective constrained dynamics. Finally, several numerical simulations are reported to show the effciency of the proposed techniques.</p></abstract>

In this paper the optimal control of alignment models composed by a large number of agents is investigated in presence of a selective action of a controller, acting in order to enhance consensus. Two types of selective controls have been presented: an homogeneous control filtered by a selective function and a distributed control active only on a selective set. As a first step toward a reduction of computational cost, we introduce a model predictive control (MPC) approximation by deriving a numerical scheme with a feedback selective constrained dynamics. Next, in order to cope with the numerical solution of a large number of interacting agents, we derive the mean-field limit of the feedback selective constrained dynamics, which eventually will be solved numerically by means of a stochastic algorithm, able to simulate effciently the selective constrained dynamics. Finally, several numerical simulations are reported to show the effciency of the proposed techniques.

Selective model-predictive control for flocking systems

Communications in Applied and Industrial Mathematics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Selective model-predictive control for flocking systems"}

In this paper the optimal control of alignment models composed by a large number of agents is investigated in presence of a selective action of a controller,...

Selective model-predictive control for flocking systems

Online veröffentlicht: 19. Dez. 2018

Seitenbereich: 4 - 21

Eingereicht: 30. Sept. 2016

Akzeptiert: 02. Feb. 2018

DOI: https://doi.org/10.2478/caim-2018-0009

Schlüsselwörter
optimal control, self-organized systems, kinetic equations, numerical modelling

© 2018 Giacomo Albi, Lorenzo Pareschi, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Selective model-predictive control for flocking systems

Online veröffentlicht: 19. Dez. 2018

Seitenbereich: 4 - 21

Eingereicht: 30. Sept. 2016

Akzeptiert: 02. Feb. 2018

DOI: https://doi.org/10.2478/caim-2018-0009

Schlüsselwörteroptimal control, self-organized systems, kinetic equations, numerical modelling

© 2018 Giacomo Albi, Lorenzo Pareschi, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
optimal control, self-organized systems, kinetic equations, numerical modelling