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Spectral analysis of extended consensus algorithms for multiagent systems
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-3248-0187
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0001-7309-8086
2014 (English)In: Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, 2014, 2204-2209 p.Conference paper (Refereed)
Abstract [en]

We analyze an extension of the well-known linear consensus protocol for agents moving in two dimensions, where the standard consensus feedback is multiplied with a rotation matrix. This leads to a richer family of trajectories, and if only the new feedback term is applied, periodic solutions emerge. For special configurations of the controller gains, the form of the system trajectories is given in terms of the eigenvalues and eigenvectors of the closed-loop system matrix. We characterize the resulting closed-loop trajectories for specific choices of the controller gains and of the communication graph topology. Furthermore, the control strategy is extended to agents with double integrator dynamics. It is shown that stability is achieved with sufficiently large velocity feedback. The effect of this feedback on the overall system performance is further investigated. We finally provide simulations to illustrate the theoretical results.

Place, publisher, year, edition, pages
2014. 2204-2209 p.
Keyword [en]
closed loop systems, control system analysis, feedback, graph theory, matrix algebra, multi-robot systems, velocity control, closed-loop system matrix, closed-loop trajectory, communication graph topology, consensus feedback, control strategy, controller gain, double integrator dynamics, extended consensus algorithm, linear consensus protocol, multiagent systems, rotation matrix, spectral analysis, velocity feedback, Aerodynamics, Eigenvalues and eigenfunctions, Equations, Laplace equations, Trajectory, Vectors, Vehicle dynamics
National Category
Control Engineering
Research subject
Electrical Engineering
URN: urn:nbn:se:kth:diva-166531DOI: 10.1109/CDC.2014.7039725ISBN: 978-1-4799-7746-8OAI: diva2:811345
2014 IEEE 53rd Annual Conference on Decision and Control (CDC), December 15-17, 2014, Los Angeles, USA

QC 20150519

Available from: 2015-05-11 Created: 2015-05-11 Last updated: 2015-05-19Bibliographically approved

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van de Hoef, SebastianDimarogonas, Dimos V.
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