Numerically efficient H∞ analysis of cooperative multi-agent systems. Issue 16 (November 2022)
- Record Type:
- Journal Article
- Title:
- Numerically efficient H∞ analysis of cooperative multi-agent systems. Issue 16 (November 2022)
- Main Title:
- Numerically efficient H∞ analysis of cooperative multi-agent systems
- Authors:
- Nakić, Ivica
Tolić, Domagoj
Tomljanović, Zoran
Palunko, Ivana - Abstract:
- Abstract: This article proposes a numerically efficient approach for computing the maximal (or minimal) impact one agent has on the cooperative system it belongs to. For example, if one is able to disturb/bolster merely one agent in order to maximally disturb/bolster the entire team, which agent to choose? We quantify the agent-to-system impact in terms of H ∞ norm whereas output synchronization is taken as the underlying cooperative control scheme. The agent dynamics are homogeneous, second order and linear whilst communication graphs are weighted and undirected. We devise simple sufficient conditions on agent dynamics, topology and output synchronization parameters rendering all agent-to-system H ∞ norms to attain their maxima in the origin (that is, when constant disturbances are applied). Essentially, we quickly identify bottlenecks and weak/strong spots in multi-agent systems without resorting to intense computations, which becomes even more important as the number of agents grows. Our analyses also provide directions towards improving communication graph design and tuning/selecting cooperative control mechanisms. Lastly, numerical examples with a large number of agents and experimental verification employing off-the-shelf nano quadrotors are provided.
- Is Part Of:
- Journal of the Franklin Institute. Volume 359:Issue 16(2022)
- Journal:
- Journal of the Franklin Institute
- Issue:
- Volume 359:Issue 16(2022)
- Issue Display:
- Volume 359, Issue 16 (2022)
- Year:
- 2022
- Volume:
- 359
- Issue:
- 16
- Issue Sort Value:
- 2022-0359-0016-0000
- Page Start:
- 9110
- Page End:
- 9128
- Publication Date:
- 2022-11
- Subjects:
- Science -- Periodicals
Technology -- Periodicals
Patents -- United States -- Periodicals
505 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/00160032 ↗ - DOI:
- 10.1016/j.jfranklin.2022.09.013 ↗
- Languages:
- English
- ISSNs:
- 0016-0032
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4755.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24205.xml