Event triggered distributed adaptive consensus control for high-order nonlinear multi-agent systems in presence of system uncertainties

Lokhande, Sanket C.; Xu, Hao; Toor, Harinder Singh

doi:10.1109/rcar.2017.8311929

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Lastly, the network implementation described here only permits one-hop communication. Previous work in this group identifies methodology for event-driven communication in similar multi-agent systems based on the communication matrix [22,23]. A combination of event-driven dynamic networking and attention-based data fusion may invite substantial gains on the simple debris collection task, or permit variations wherein the size or clutter of the region of interest would impose greater demands.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Intelligent collaborative sensing for detection and removal of small distributed space debris

Dailey

Connolly

Lokhande

et al. 2023

Sensors and Systems for Space Applications XVI

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Space debris in the 1-10 cm diameter regime presents a particular hazard to future operations in low Earth orbit (LEO). These objects are too small to be reliably detected by terrestrial radar or telescopes, but too large for their impacts to be mitigated with Whipple shielding. This paper addresses this hazard by presenting a methodology for space-based detection and active debris removal (ADR) via novel intelligent collaborative sensing and efficient decentralized data fusion. In simulation, we demonstrate that a small heterogeneous constellation of co-orbiting satellites using attentional neural networks can autonomously share information and maneuver in a cooperative game to de-orbit space debris (e.g. with a mechanical arm or pulsed laser) while minimizing total energy consumption and collision risk in the constellation. Particular focus is given to the robustness and effectiveness of the developed collaborative sensing system with respect to sensor uncertainties and transient changes in observability between nodes.

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Section: Limitations and Future Workmentioning

confidence: 99%

Intelligent collaborative sensing for detection and removal of small distributed space debris

Dailey

Connolly

Lokhande

et al. 2023

Sensors and Systems for Space Applications XVI

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Adversarial Swarm Defence Using Multiple Fixed-Wing Unmanned Aerial Vehicles

Choi¹,

Seo

Shin

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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This paper proposes a novel coverage-based adversarial swarm defence algorithm. The defender swarm composed of fixed-wing unmanned aerial vehicles (UAVs) is assumed to have explosives onboard to intercept an adversarial swarm. The proposed approach consists of two steps: i) impact point optimization and ii) model predictive control (MPC)-based impact time control. The impact point optimization periodically optimizes impact points for the corresponding UAVs to maximize the coverage within the hostile swarm while minimizing the common impact time. The optimization domain is limited to a physically reachable area of UAVs with the common impact time. Besides, the MPC-based impact time controller is designed to ensure the multiple UAVs to arrive the generated time-varying impact points simultaneously. Numerical simulations are performed to prove the feasibility and efficiency of the proposed swarm defence algorithm.

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Event triggered distributed adaptive consensus control for high-order nonlinear multi-agent systems in presence of system uncertainties

Cited by 2 publications

References 24 publications

Intelligent collaborative sensing for detection and removal of small distributed space debris

Intelligent collaborative sensing for detection and removal of small distributed space debris

Adversarial Swarm Defence Using Multiple Fixed-Wing Unmanned Aerial Vehicles

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