Collective circular motion in synchronized and balanced formations with second-order rotational dynamics

Jain, Ankita; Ghose, Debasish

doi:10.1016/j.cnsns.2017.05.029

Cited by 34 publications

(18 citation statements)

References 32 publications

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“…The stability of (18) is guaranteed under the condition that the communication network is circulant [3,16]. A circulant network is completely defined by its first row and each subsequent row is the previous row shifted one position to the right with the first entry of the row equal to the last entry of the previous row.…”

Section: Particles With Coupled-oscillator Dynamicsmentioning

confidence: 99%

“…Jain and Ghose [3] stabilized their models to formations whose centroid converges to a desired spatial coordinate. Besides, the radii of the circular formations may vary for each agent, with the same (or not) center of rotation, and is divided into synchronization subgroups.…”

Section: Introductionmentioning

confidence: 99%

“…Phase-coupled oscillators may be employed to model several systems of interacting individuals, such as neurons in a brain, coupled pendulums, groups of living beings [1] and applications of collective motion [2,3]. One of the most prominent paradigms of the field of phase-coupled oscillators is the Kuramoto model [4], in which the oscillators' interactions are mediated via sinusoidal coupling.…”

Section: Introductionmentioning

confidence: 99%

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Collision Avoidance Mechanism for Symmetric Circular Formations of Unitary Mass Autonomous Vehicles at Constant Speed

Freitas

Macau

2018

Mathematical Problems in Engineering

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Collective motion is a promising field that studies how local interactions lead groups of individuals to global behaviors. Biologists try to understand how those subjects interplay in nature, and engineers are concerned with the application of interaction strategies to mobile vehicles, satellites, robots, etc. There are several models in literature that employ strategies observed in groups of beings in nature. The aim is not to literally mimic them but to extract suitable strategies for the chosen application. These models, constituted of multiple mobile agents, can be used in tasks such as data collection, surveillance and monitoring. One approach is to use phasecoupled oscillators to design the mobile agents, in which each member is an oscillator and they are coupled according to an interconnection network. This design usually does not keep track and handle the possible collisions within the group, and real applications obviously must manage these situations to prevent the equipment from crashing. This paper introduces a collision avoidance mechanism to a model of particles with phase-coupled oscillators dynamics for symmetric circular formations.

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Section: Particles With Coupled-oscillator Dynamicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Collision Avoidance Mechanism for Symmetric Circular Formations of Unitary Mass Autonomous Vehicles at Constant Speed

Freitas

Macau

2018

Mathematical Problems in Engineering

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“…Under the same conditions of Theorem 8, with the circular motion control law (22) and phase control laws (20) and (23), all the agents will be enforced to converge to a circular formation as described in Theorem 8 and the phases of agent can be steered to their desired phase * for = 2, . .…”

Section: Corollarymentioning

confidence: 99%

“…The circular formation is a design method for steering the agents to orbit around a target along a common circle, which provides a simple geometric shape to collect data with a desired spatial and temporal distribution. In the community of systems and control, research efforts have been devoted to the circle formation problem for multiagent systems modeled as single or double integrators [14][15][16][17][18] and unicycles [19][20][21][22][23][24][25][26] under different communication topologies. Circular motion has been studied in the scenario of cyclic pursuit with ring topology [14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Circular Formation Control of Multiagent Systems with Any Preset Phase Arrangement

Jin

Dongxu

2018

Journal of Control Science and Engineering

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This paper deals with the circular formation control problem of multiagent systems for achieving any preset phase distribution. The control problem is decomposed into two parts: the first is to drive all the agents to a circle which either needs a target or not and the other is to arrange them in positions distributed on the circle according to the preset relative phases. The first part is solved by designing a circular motion control law to push the agents to approach a rotating transformed trajectory, and the other is settled using a phase-distributed protocol to decide the agents' positioning on the circle, where the ring topology is adopted such that each agent can only sense the relative positions of its neighboring two agents that are immediately in front of or behind it. The stability of the closed-loop system is analyzed, and the performance of the proposed controller is verified through simulations.

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Time‐varying group formation‐tracking control for general linear multi‐agent systems with switching topologies and unknown input

Dong

et al. 2022

Intl J Robust & Nonlinear

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Time-varying group formation tracking problems for general linear multi-agent systems with unknown control input and switching topologies are studied. There are two kinds of agents, leaders and followers. Leaders with unknown control input can generate unpredictable and maneuverable trajectories. Followers accomplish macroscopic moving guided by single or multiple leaders of respective subgroups and keep desired time-varying sub-formations simultaneously. Agents are assigned in groups and interactions within or between groups both exist owning to the design of Laplacian matrix. First, the time-varying group formation tracking problem is described and group division is analyzed through adjustment of properties in Laplacian matrix. Then the control protocols based on neighboring interaction relationships are introduced. Influence of unknown control input from leaders can be handled and information is delivered effectively so that followers can accomplish expected formations. An algorithm is given to determine control parameters and the formation tracking feasible constraint is presented. Next the stability of the multi-agent system with group division is proved, which means the general linear multi-agent system can accomplish time-varying group formation tracking with unknown control input and switch topologies under designed protocols. At last, a numerical simulation is given to verify the effectiveness of presented theoretical results.

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Collective circular motion in synchronized and balanced formations with second-order rotational dynamics

Cited by 34 publications

References 32 publications

Collision Avoidance Mechanism for Symmetric Circular Formations of Unitary Mass Autonomous Vehicles at Constant Speed

Collision Avoidance Mechanism for Symmetric Circular Formations of Unitary Mass Autonomous Vehicles at Constant Speed

Circular Formation Control of Multiagent Systems with Any Preset Phase Arrangement

Time‐varying group formation‐tracking control for general linear multi‐agent systems with switching topologies and unknown input

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