Generalized Cyclic Pursuit: An Estimator-Based Model-Reference Adaptive Control Approach

Ansart, Antoine; Juang, Jyh‐Ching

doi:10.1109/med48518.2020.9183218

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…One stream of research on cyclic pursuit focuses on formations that realize rendezvous or maintain a constant or dynamic inter-agent spacing while rotating around a fixed or mobile target [11][12][13][14][15][16][17][18][19]. Another stream focuses on the generation of non-circular formation patterns by using modified cyclic pursuit strategies [20][21][22][23][24]. A generalized cyclic pursuit (GCP) scheme was used in the above-referenced studies as the primary formation control tool, and it was demonstrated that this scheme could produce epicyclic or spirograph-like motions among a group of agents.…”

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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“…In addition, the work conducted in [25] deals with synchronization of MAS by using weightage based on local information. Recently, the authors in [26,27] use model reference adaptive control on a MAS under generalized cyclic pursuit scheme to maintain the formation despite the present uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Integral Sliding Control Approach for Generalized Cyclic Pursuit Formation Maintenance

Ansart

Juang

2021

Electronics

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This paper is concerned with the formation maintenance of a group of autonomous agents under generalized cyclic pursuit (GCP) law. The described pattern for agents under such formation is epicycle-like. For a network of agents to achieve such a formation, marginal stability of the overall network is required. The desired marginal stability of the network relies on each agents’ gain values, and uncertainties in these gains can occur. Previous studies have used fixed gains, we enhance the stability of the gains via a dynamic approach using an integral sliding controller (ISC). An ISC can ensure sliding behavior of the gains throughout the entire response, and it is shown that the gains are robust toward variations and thus make the network keep its marginal stability and its formation.

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“…Examples of dynamical control by the application of adaptive approaches for cyclic chase were antecedently covered. The researchers in [26,27] use model reference adaptive control on a MAS under generalized cyclic pursuit (GCP) scheme to keep the formation notwithstanding the current uncertainty. Further, the development of an Integral sliding mode controller (ISC) for GCP was approached with the aim of sustaining the motion [28].…”

Section: Introductionmentioning

confidence: 99%

Robust Formation Maintenance Methods under General Topology Pursuit of Multi-Agents Systems

2021

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In this article, methods of formation maintenance for a group of autonomous agents under ageneral topology scheme are discussed. Unlike rendezvous or geometric formation, general topology pursuit allows the group of agents to autonomously form trochoid patterns, which are useful in civilian and military applications. However, this type of topology is established by designing a marginally stable system that may be sensitive to parameter variations. To account for this drawback of stability, linear fixed-gains are turned into a dynamical version in this paper. By implementing a disturbance observer controller, systems are shown to maintain their formation despite the disturbances or uncertainties. Comparison in the effectiveness of the presented method with model reference adaptive control and integral sliding mode control under the uncertainties of the gains is also conducted. The capabilities of controllers are demonstrated and supported through simulations.

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Generalized Cyclic Pursuit: An Estimator-Based Model-Reference Adaptive Control Approach

Cited by 5 publications

References 14 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

Integral Sliding Control Approach for Generalized Cyclic Pursuit Formation Maintenance

Robust Formation Maintenance Methods under General Topology Pursuit of Multi-Agents Systems

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