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Proceedings ArticleDOI

Collective behavior with heterogeneous controllers

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TLDR
It is shown that, by selecting suitable controller gains, these formations can be controlled significantly to obtain not only a desired direction of motion but also a desired location of the centroid.
Abstract
In this paper, we study the collective motion of individually controlled planar particles when they are coupled through heterogeneous controller gains. Two types of collective formations, synchronization and balancing, are described and analyzed under the influence of these heterogeneous controller gains. These formations are characterized by the motion of the centroid of the group of particles. In synchronized formation, the particles and their centroid move in a common direction, while in balanced formation the movement of particles possess a fixed location of the centroid. We show that, by selecting suitable controller gains, these formations can be controlled significantly to obtain not only a desired direction of motion but also a desired location of the centroid. We present the results for N-particles in synchronized formation, while in balanced formation our analysis is confined to two and three particles.

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Journal ArticleDOI

Synchronization of multi-agent systems with heterogeneous controllers

TL;DR: In this paper, the effect of heterogeneous controller gains on the common velocity direction at which the system of agents synchronizes is analyzed and conditions under which heterogeneous controllers result in a synchronized formation are derived and it is shown that the result lies in the conic hull of the initial velocity vectors of agents.
Journal ArticleDOI

Stabilization of collective formations with speed and controller gain heterogeneity and saturation

TL;DR: This paper studies collective formations of multi-agent systems, modeled with unicycle dynamics, while admitting heterogeneity in both controller gains and speeds of the agents along with saturation on the controller outputs to address a practical scenario where the speeds are usually nonidentical and the controller gains may vary due to imperfect implementation.
Proceedings ArticleDOI

Achieving a desired collective centroid by a formation of agents moving in a controllable force field

TL;DR: In this article, an all-to-all coupled planar motion model is proposed to solve the problem of a formation of agents trying to achieve a desired stationary or moving collective centroid.
Posted Content

Collective Circular Motion of Multi-Agent Systems in Synchronized and Balanced Formations With Second-Order Rotational Dynamics

TL;DR: This paper considers the collective circular motion of multi-agent systems in which all the agents are required to traverse different circles or a common circle at a prescribed angular velocity, and presents suitable feedback control laws by considering a second-order rotational dynamics of the agent.
Posted Content

Phase Balancing of Two and Three-Agent Heterogeneous Gain Systems With Extensions to Multiple Agents.

TL;DR: By using heterogeneity controller gains, the velocity directions of the agents in balanced formation can be controlled by using heterogeneous controller gains and the effect of heterogeneous gains on the reachable set of these velocity directions is analyzed.
References
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Consensus and Cooperation in Networked Multi-Agent Systems

TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
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From Kuramoto to Crawford: exploring the onset of synchronization in populations of coupled oscillators

TL;DR: In this article, the authors review 25 years of research on the Kuramoto model, highlighting the false turns as well as the successes, but mainly following the trail leading from Kuramoto's work to Crawford's recent contributions.
BookDOI

Distributed Consensus in Multi-vehicle Cooperative Control

Wei Ren, +1 more
TL;DR: In this article, the authors present a survey of the use of consensus algorithms in multi-vehicle cooperative control, including single-and double-integrator dynamical systems, rigid-body attitude dynamics, rendezvous and axial alignment, formation control, deep-space formation flying, fire monitoring and surveillance.
Journal ArticleDOI

Collective Motion, Sensor Networks, and Ocean Sampling

TL;DR: This paper addresses the design of mobile sensor networks for optimal data collection by using a performance metric, used to derive optimal paths for the network of mobile sensors, to define the optimal data set.
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