TY - GEN
T1 - Alignment as biological inspiration for control of multi agent systems
AU - Rastgoftar, Hossein
AU - Jayasuriya, Suhada
N1 - Publisher Copyright:
Copyright © 2014 by ASME.
PY - 2014
Y1 - 2014
N2 - In this paper, we develop a framework for evolution of a multi agent systems (MAS) under local perception. The idea of this paper comes from natural biological swarms where agents adjust their behavior based on individual perception of the behavior of its neighbors. Most available engineered swarms rely on local communication where an individual agent needs exact state information of its adjacent agents to evolve. We consider agents of a MAS to be particles of a continuum (deformable Body) transforming under a homogenous mapping. Homogenous transformations have the property that two crossing straight lines in an initial configuration translate as two different crossing straight lines. We will consider this feature of homogenous mappings to show how certain desired objectives can be achieved by agents of a swarm by preserving alignment among nearby agents. We show that evolution of a MAS under this alignment strategy can be achieved where agents don't need to know the exact positions of the adjacent agents nor do they need peer to peer communication.
AB - In this paper, we develop a framework for evolution of a multi agent systems (MAS) under local perception. The idea of this paper comes from natural biological swarms where agents adjust their behavior based on individual perception of the behavior of its neighbors. Most available engineered swarms rely on local communication where an individual agent needs exact state information of its adjacent agents to evolve. We consider agents of a MAS to be particles of a continuum (deformable Body) transforming under a homogenous mapping. Homogenous transformations have the property that two crossing straight lines in an initial configuration translate as two different crossing straight lines. We will consider this feature of homogenous mappings to show how certain desired objectives can be achieved by agents of a swarm by preserving alignment among nearby agents. We show that evolution of a MAS under this alignment strategy can be achieved where agents don't need to know the exact positions of the adjacent agents nor do they need peer to peer communication.
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U2 - 10.1115/dscc2014-6141
DO - 10.1115/dscc2014-6141
M3 - Conference contribution
AN - SCOPUS:84929340496
T3 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
BT - Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems
PB - American Society of Mechanical Engineers
T2 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Y2 - 22 October 2014 through 24 October 2014
ER -