Generalized hierarchical cyclic pursuit

Mukherjee, Dwaipayan; Ghose, Debasish

doi:10.1016/j.automatica.2016.05.023

Cited by 20 publications

(6 citation statements)

References 15 publications

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“…This strategy is frequently used in cases where multiple agents must move in a coordinated manner, for instance, to entrap a target, conduct patrolling and surveillance operations, and seek sources in a sensed environment (see [1] and the references therein). The method-based classification of schemes implemented in circular formation control is as follows: leader-follower method [2][3][4], artificial potential method [5], behavior-based method [6,7], virtual structure method [8,9], event-triggered control method [10], and cyclic pursuit method [11][12][13][14][15][16][17][18][19][20]. Among these schemes, the cyclic pursuit method has attracted considerable attention because of its intrinsic benefits resulting from its minimal communication requirements for connectivity.…”

Section: Introductionmentioning

confidence: 99%

Graphical and Analytical Approaches for Analyzing Collective Behavior of Dynamic Multi-Agent Systems Governed by Generalized Cyclic Pursuit Mechanism

Kwak,

Kim,

Hori

et al. 2023

IEEE Access

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In this study, we use graphical and analytical methods to study the collective behavior of a swarm of dynamic agents controlled by the generalized cyclic pursuit (GCP) scheme. The proposed graphical approach reveals the occurrence mechanisms of various formation patterns in terms of agents' dynamics and tuning parameters of the GCP scheme, including the rendezvous, diverging spirals, circular pattern, and spirograph-like patterns. Then, we develop an analytical tool to obtain the crucial information needed to formulate expressions of the circular and spirograph-like steady-state trajectories generated by the GCP-controlled dynamic multi-agent system. In addition, the steady-state formation trajectories of a swarm of dynamic agents are formulated by explicitly considering the agents' general continuous-time linear timeinvariant model and the scenario in which more than two pairs of closed-loop poles exist on the imaginary axis of the complex plane. Numerical simulation cases of the GCP-controlled dynamic multi-agent system are presented to demonstrate the effectiveness of the proposed analysis methodology.

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Section: Introductionmentioning

confidence: 99%

Graphical and Analytical Approaches for Analyzing Collective Behavior of Dynamic Multi-Agent Systems Governed by Generalized Cyclic Pursuit Mechanism

Kwak,

Kim,

Hori

et al. 2023

IEEE Access

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“…A similar extension holds for more levels. It was shown that hierarchical control leads to an increased rate of convergence [Mukherjee and Ghose, 2016]. Besides the trade-off between system performance and resource demands, some papers focus on handling the system failures occurring due to switching topologies, communication delays, and unpredicted malfunctions [Schiffer et al, 2017].…”

Section: Introductionmentioning

confidence: 99%

A new method of adaptive mesoscale control in complex multiagent networked dynamical systems

Amelin

Granichin

Леонова

et al. 2022

CAP

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Centralized strategies applied to large-scale systems require a vast amount of computational and communication resources. In contrast to them, distributed strategies offer higher scalability and reliability. However, communication and coordination among agents tremendously impact performance of systems controlled in the distributed manner. The existing methods lead to clustering, where the coordination between agents is limited to groups of entities to be controlled. The size of these groups are usually known in advance. In turn, many systems exhibit self-organization and dynamically form clustering structure. In that sense, control methods should adapt to such dynamic structures offering the same balance between performance and communication/computational demands. In this paper, we propose a new approach to complex system control based on efficient cluster (mesoscopic) control paradigm. We demonstrate its efficacy in scenarios, where a group of agents should reach a certain goal.

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“…The cyclic pursuit is a strategy where agent i pursues its neighbor i − 1 , while agent 1 pursues agent n, thus the topology of communication is a Hamiltonian cycle. The extensions to hierarchical structures are considered in [10] and [11]; [12] addresses the case of heterogeneous agents; geometrical problems related to cyclic pursuit-like algorithms are investigated in [13] and [14]. Some pursuit algorithms utilize the rotation operator in order to follow the desired trajectories, see [15] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Second-Order Agents on Ring Digraphs

Parsegov

Chebotarev

2018

2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)

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The paper addresses the problem of consensus seeking among second-order linear agents interconnected in a specific ring topology. Unlike the existing results in the field dealing with one-directional digraphs arising in various cyclic pursuit algorithms or two-directional graphs, we focus on the case where some arcs in a two-directional ring graph are dropped in a regular fashion. The derived condition for achieving consensus turns out to be independent of the number of agents in a network.

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Generalized hierarchical cyclic pursuit

Cited by 20 publications

References 15 publications

Graphical and Analytical Approaches for Analyzing Collective Behavior of Dynamic Multi-Agent Systems Governed by Generalized Cyclic Pursuit Mechanism

Graphical and Analytical Approaches for Analyzing Collective Behavior of Dynamic Multi-Agent Systems Governed by Generalized Cyclic Pursuit Mechanism

A new method of adaptive mesoscale control in complex multiagent networked dynamical systems

Second-Order Agents on Ring Digraphs

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