https://doi.org/10.1140/epjb/s10051-021-00163-2
Regular Article - Statistical and Nonlinear Physics
Linear nearest neighbor flocks with all distinct agents
1
Digimarc Corporation, 9405 SW Gemini Drive, 97008-7192, Beaverton, OR, USA
2
Fariborz Maseeh Department of Mathematics and Statistics, Portland State University, Portland, USA
Received:
22
February
2021
Accepted:
13
July
2021
Published online:
23
August
2021
This paper analyzes the global dynamics of one-dimensional agent arrays with nearest neighbor linear couplings. The equations of motion are second-order linear ODE’s with constant coefficients. The novel part of this research is that the couplings are different for each distinct agent. We allow the forces to depend on the positions and velocity (damping terms) but the magnitudes of both the position and velocity couplings are different for each agent. We, also, do not assume that the forces are “Newtonian” (i.e. the force due to A on B equals the minus the force of B on A) as this assumption does not apply to certain situations, such as traffic modeling. For example, driver A reacting to driver B does not imply the opposite reaction in driver B. There are no known analytical means to solve these systems, even though they are linear, and so relatively little is known about them. This paper is a generalization of previous work that computed the global dynamics of one-dimensional sequences of identical agents (Cantos et al., Eur Phys J Special Topics 225:1115–1125, 2016) assuming periodic boundary conditions. In this paper, we push that method further, similar to Baldivieso and Veerman, IEEE Trans Control Network Syst (2021), and use an extended periodic boundary condition to to gain quantitative insights into the systems under consideration. We find that we can approximate the global dynamics of such a system by carefully analyzing the low-frequency behavior of the system with (generalized) periodic boundary conditions.
© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2021