TR2017-091

Distributed Extremum Seeking in Multi-Agent Systems with Arbitrary Switching Graphs


    •  Poveda, J., Benosman, M., Teel, A., "Distributed Extremum Seeking in Multi-Agent Systems with Arbitrary Switching Graphs", World Congress of the International Federation of Automatic Control (IFAC), DOI: 10.1016/​j.ifacol.2017.08.240, July 2017, vol. 50, pp. 735-740.
      BibTeX TR2017-091 PDF
      • @inproceedings{Poveda2017jul,
      • author = {Poveda, Jorge and Benosman, Mouhacine and Teel, Andy},
      • title = {Distributed Extremum Seeking in Multi-Agent Systems with Arbitrary Switching Graphs},
      • booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
      • year = 2017,
      • volume = 50,
      • number = 1,
      • pages = {735--740},
      • month = jul,
      • publisher = {Elsevier},
      • doi = {10.1016/j.ifacol.2017.08.240},
      • url = {https://www.merl.com/publications/TR2017-091}
      • }
  • Research Area:

    Dynamical Systems

Abstract:

This paper studies the problem of averaging-based extremum seeking in dynamical multi-agent systems with time-varying communication graphs. We consider a distributed consensus-optimization problem where the plants and the controllers of the agents share information via time-varying graphs, and where the cost function to be minimized corresponds to the summation of the individual response maps generated by the agents. Although the problem of averaging-based extremum seeking control in multi-agent dynamical systems with timeinvariant graphs has been extensively studied, the case where the graph is time-varying remains unexplored. In this paper we address this problem by making use of recent results for generalized set-valued hybrid extremum seeking controllers, and the framework of switched differential inclusions and common Lyapunov functions. For the particular consensus-optimization problem considered in this paper, a semi-global practical stability result is established. A numerical example in the context of dynamic electricity markets illustrates the results.