4.7 Article

Time-Varying Formation for General Linear Multiagent Systems Over Directed Topologies: A Fully Distributed Adaptive Technique

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2018.2877818

Keywords

Adaptive control; directed topology; multiagent system; time-varying formation

Funding

  1. National Nature Science Foundation of China [61603301, 61603300, 61722303, 61673104]
  2. China Post-Doctoral Science Foundation [2017M623244, 2018T111097, 2018M633575]
  3. Natural Science Foundation of Shaanxi Province of China [2017JQ6016, 2018JQ6073, 2018JQ6071]
  4. Fundamental Research for Science and Technology Planning Project of Shenzhen [JCYJ20170306153912850]
  5. Natural Science Foundation of Jiangsu Province of China [BK20170079]
  6. Australian Research Council [DE180101268]
  7. Fundamental Research Funds for the Central Universities of China [3102018jcc038, 2242018k1G004, 20103176478]
  8. Source Innovation Program of Qindao [18-2-2-39-jch]

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This paper investigates the time-varying formation problem under directed topologies and develops a fully distributed formation controller for general linear multiagent systems. By using adaptive techniques and analyzing Lyapunov stability, a fully distributed formation algorithm that relies only on local measurements is designed to achieve time-varying formations.
In this paper, the time-varying formation problem is studied under directed topologies. An adaptive approach is utilized to develop a fully distributed formation controller for general linear multiagent systems. To achieve distributed time-varying formations, a feasible formation set is proposed by proposing some conditions. By using adaptive techniques, the main contribution of this paper is that a fully distributed formation algorithm is designed for achieving time-varying formation under directed graphs, which relies only on the local measurements without requiring any global information. By analyzing the Lyapunov stability, the proposed fully distributed formation algorithm can ensure the multiagent systems achieving the goal of time-varying formations. To verify the theoretical results, some simulation examples are shown finally.

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