Title :
Distributed allocation of mobile sensing agents in geophysical flows
Author :
Hsieh, M. Ani ; Mallory, Kenneth ; Forgoston, Eric ; Schwartz, Ira B.
Author_Institution :
Mech. Eng. & Mech. Dept., Drexel Univ., Philadelphia, PA, USA
Abstract :
We address the synthesis of distributed control policies to enable a homogeneous team of mobile sensing agents to maintain a desired spatial distribution in a geophysical flow environment. Geophysical flows are natural large-scale fluidic environments such as oceans, eddies, jets, and rivers. In this work, we assume the agents have a “map” of the fluidic environment consisting of the locations of the Lagrangian coherent structures (LCS). LCS are time-dependent structures that divide the flow into dynamically distinct regions, and are time-dependent extensions of stable and unstable manifolds. Using this information, we design agent-level hybrid control policies that leverage the surrounding fluid dynamics and inherent environmental noise to enable the team to maintain a desired distribution in the workspace. We validate the proposed control strategy using flow fields given by: 1) an analytical time-varying wind-driven multi-gyre flow model, 2) actual flow data generated using our coherent structure experimental testbed, and 3) ocean data provided by the Navy Coastal Ocean Model (NCOM) database.
Keywords :
geophysics computing; mobile agents; LCS; Lagrangian coherent structures; NCOM database; agent-level hybrid control policies; analytical time-varying wind-driven multi-gyre flow model; control strategy; distributed allocation; distributed control policies; environmental noise; flow data; flow fields; fluid dynamics; geophysical flow environment; geophysical flows; homogeneous team; jets; large-scale fluidic environments; mobile sensing agents; navy coastal ocean model; ocean data; rivers; spatial distribution; time-dependent structures; unstable manifolds; Manifolds; Mobile communication; Oceans; Resource management; Sensors; Sociology; Vehicle dynamics; (Under)water vehicles; Autonomous systems; Cooperative control;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859084