Gradient Free Source-Seeking Using Flocking Behavior

Turgeman, Avi; Datar, Adwait; Werner, Herbert

doi:10.23919/acc.2019.8815372

Cited by 4 publications

(2 citation statements)

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“…Planar motion with a swarm of agents in a given formation that converges and moves along a level curve was investigated in Reference 21. A degree of flexibility is achieved when solving the source seeking or level curve tracking problem using flocking control 22 …”

Section: Introductionmentioning

confidence: 99%

“…A degree of flexibility is achieved when solving the source seeking or level curve tracking problem using flocking control. 22 In Reference 23, an underwater source seeking scenario with a swarm of autonomous underwater vehicles is considered. For this purpose an LPV model of the Hippocampus autonomous underwater vehicle, developed at TUHH, 24 is used for controller design and simulation.…”

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Distributed control for complex missions: Quasi‐linear parameter varying approach

Attallah

Werner

2022

Intl J Robust & Nonlinear

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A distributed flocking control scheme is presented for a swarm of non-holonomic vehicles modeled as linear parameter varying (LPV) systems.The vehicles are assumed to perform tasks that arise when exploring scalar fields on R 3 , which may represent, for example, concentration levels of a toxic substance in air or water. Here we consider in particular level surface tracking and level surface monitoring missions. It is assumed that agents can sense gradient and Hessian information of the scalar field at their current position. The control architecture of each vehicle is structured into two modules: a flocking filter which represents a virtual layer of the network, and local tracking controllers for vehicles on the physical layer. The flocking filter receives data from neighboring vehicles and generates a reference signal. An LPV tracking controller for the vehicles, and a network flocking filter that stabilizes the whole network, are designed separately. Simulated mission scenarios with swarm of autonomous underwater vehicles demonstrate the practicality of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%