Consensus for linear agents with unknown parameters
Consensus for linear agents with unknown parameters
We solve consensus problems for networks of identical linear agents whose dynamics is unknown except for the order. We estimate the unknown dynamics via an “extended state-observer”, and cancel it with a suitably designed control. The agent dynamics is thus approximated by that of an n-integrator, and standard protocols for networks of such type can then be used to achieve consensus for the network of original unknown agents.
2505-2510
Rapisarda, P.
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Sira-Ramirez, H.
287633e7-43b9-4e2a-86d9-78f317eb39fd
Savva, R.
f57609b3-9670-4777-9292-206078c21b4d
Rapisarda, P.
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Sira-Ramirez, H.
287633e7-43b9-4e2a-86d9-78f317eb39fd
Savva, R.
f57609b3-9670-4777-9292-206078c21b4d
Rapisarda, P., Sira-Ramirez, H. and Savva, R.
(2017)
Consensus for linear agents with unknown parameters.
IFAC-PapersOnLine, 50 (1), .
(doi:10.1016/j.ifacol.2017.08.448).
Abstract
We solve consensus problems for networks of identical linear agents whose dynamics is unknown except for the order. We estimate the unknown dynamics via an “extended state-observer”, and cancel it with a suitably designed control. The agent dynamics is thus approximated by that of an n-integrator, and standard protocols for networks of such type can then be used to achieve consensus for the network of original unknown agents.
Text
Consensus for linear agents with unknown parameters
- Accepted Manuscript
More information
Accepted/In Press date: 28 February 2017
e-pub ahead of print date: 18 October 2017
Venue - Dates:
20th IFAC World congress, , Toulouse, France, 2017-07-09 - 2017-07-14
Organisations:
Vision, Learning and Control
Identifiers
Local EPrints ID: 407679
URI: http://eprints.soton.ac.uk/id/eprint/407679
ISSN: 2405-8963
PURE UUID: 921c1e61-b0b2-4f36-974a-0b0b37209b46
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Date deposited: 22 Apr 2017 01:04
Last modified: 16 Mar 2024 05:56
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Contributors
Author:
P. Rapisarda
Author:
H. Sira-Ramirez
Author:
R. Savva
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