Stability analysis of swarms

By Veysel Gazi, Kevin M. Passino. Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2002

1,036 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/7806a70511d73a7b4f0b3b156aebf374d0998f2d

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Citations in the corpus

State Transitions and the Continuum Limit for a 2D Interacting, Self-Propelled Particle System (2006, background): “It is interesting to note that this equation arises in the context of a gradient flow algorithm for autonomous vehicle control [8,35,36,37].”
Abstraction and control for Groups of robots (2004, background): “Finally, to limit the amount of interrobot communication in the overall control architecture, we want to achieve an architecture where the control law of a robot only depends on its own state and the low-dimensional state of the team from the group manifold, as follows: (14)”
Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning (2014, neutral): “G The framework builds on a dynamic model formulation [52], to employ pairwise distance dependent functions and a neighborhood characterized graph to control the grouping of similar vertex maps.”
State Agreement for Continuous-Time Coupled Nonlinear Systems (2007, background): “Examples are abundant in biology, physics, engineering, ecology, and social science: e.g., a biochemical reaction network [14], coupled Kuramoto oscillators [17, 39], arrays of chaotic systems [44, 45], a swarm of organisms [12, 13], and a group of autonomous agents [16, 22, 23].”
Motion Coordination with Distributed Information (2007, neutral): “This objective function and its variations are employed over diﬀerent proximity graphs in a number of works in the literature ([20] and [21] over the complete graph, [17] over the r -disk graph) to guarantee collision avoidance and cohesiveness of the mobile network.”
Flocking of multi-agent systems with a dynamic virtual leader (2009, background): “…without centralised coordination and control (Reynolds 1987; Vicsek, Czirok, Ben-Jacob, Cohen and Shochet 1995; Leonard and Fiorelli 2001; Gazi and Passino 2003; Jadbabaie, Lin and Morse 2003; Tanner, Jadbabaie and Pappas 2003, 2007; Fax and Murray 2004; Lin, Broucke and Francis 2004;…”
Formations of vehicles in cyclic pursuit (2004, background): “, see [16], [17], and the references therein).”
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms (2009, background): “, 2006), swarm aggregation (Gazi and Passino, 2003), gradient climbing (Ögren et al.”
Consensus for multi‐agent systems under double integrator dynamics with time‐varying communication delays (2012, background): “INTRODUCTION Recently, distributed coordination among multiple agents has become a hot issue in the control community because of its broad applications [1, 2].”
Lp theory for the multidimensional aggregation equation (2011, background): “3) arises in a number of models for biological aggregation [11, 14, 15, 23, 28, 37, 36, 38, 39] as well as problems in materials science [24, 25] and granular media [3, 17, 18, 31, 40].”
Forced consensus in networks of double integrator systems with delayed input (2010, neutral): “…the potential broad applications in various areas, including congestion control in communication networks, cooperative control of multiple vehicle systems, formation control, swarming and flocking (Gazi & Passino, 2003, 2004; Tanner&Christodoulakis, 2007; Tanner, Jadbabaie, & Pappas, 2007).”
On the controllability of nearest neighbor interconnections (2004, background): “Another class of coordination algorithms uses potential functions to express the group task [3], [4], [5].”
Formation controllability of high-order linear time-invariant swarm systems (2010, methodology): “It intuitively corresponds to the attraction/repulsion relationship in a first-order system [23]: for example if F is Hurwitz, in an unforced swarm system this relationship can be regarded as being attractive.”
Semi-Global Leader-Following Consensus of Linear Multi-Agent Systems With Input Saturation via Low Gain Feedback (2013, background): “Other topics that are highly relevant to consensus are synchronization [4]–[14], swarming [15], [16], flocking [17]–[20] and rendezvous [21].”
Distributed Control of Robotic Networks (2009, background): “, 2006], swarm aggregation [Gazi and Passino, 2003], gradient climbing [Ögren et al.”