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Communication Dans Un Congrès Année : 2015

Global extremum seeking by Kriging with a multi-agent system

Résumé

This paper presents a method for finding the global maximum of a spatially varying field using a multi-agent system. A surrogate model of the field is determined via Kriging (Gaussian process regression) from a set of sampling measurements collected by the agents. A criterion exploiting Kriging statistical properties is introduced for selecting new sampling points that each vehicle must rally. These new points are obtained as a compromise between improvement of the estimate of the global maximum and traveling distance. A cooperative control law is proposed to move the agents to the desired sampling positions while avoiding collisions. Simulation results show the interest of the method and how it compares with a state-of-art solution.
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Dates et versions

hal-01170131 , version 1 (01-07-2015)
hal-01170131 , version 2 (21-07-2015)

Identifiants

  • HAL Id : hal-01170131 , version 1

Citer

Arthur Kahn, Julien Marzat, Hélène Piet-Lahanier, Michel Kieffer. Global extremum seeking by Kriging with a multi-agent system. 17th IFAC Symposium on System Identification, SYSID 2015, Oct 2015, Beijing, China. ⟨hal-01170131v1⟩
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