# Sparse Control of Kinetic Cooperative Systems to Approximate Alignment

## TL;DR

This paper introduces a simple, robust, and sparse control strategy for kinetic cooperative systems that guides the system towards approximate alignment, relying only on minimal information and applicable regardless of the number of agents.

## Contribution

The authors develop a novel control method for kinetic cooperative systems that is sparse, constructive, and independent of the number of agents, facilitating practical applications.

## Key findings

- Control strategy effectively steers systems towards alignment
- Method requires only support size and Lipschitz constant
- Applicable to large-scale and infinite-agent systems

## Abstract

Cooperative systems are systems in which the forces among agents are non-repulsive. The free evolution of such systems can tend to the formation of patterns, such as consensus or clustering, depending on the properties and intensity of the interaction forces between agents. The kinetic cooperative systems are obtained as the mean field limits of these systems when the number of agents goes to infinity. These limit dynamics are described by transport partial differential equations involving non-local terms. In this article, we design a simple and robust control strategy steering any kinetic cooperative system to approximate alignment. The computation of the control at each instant will only require knowledge of the size of the support of the crowd in the phase space and of the Lipschitz constant of the interaction forces. Besides, the control we apply to our system is sparse, in the sense that it acts only on a small portion of the total population at each time. It also presents the features of being obtained through a constructive procedure and to be independent on the number of agents, making it convenient for applications.