Adaptive-extremum seeking control algorithm to seek the odor source using a multi-agent system

This study aims to seek the odor source using a multi-agent system. The main challenge of the odor source seeking is to search the optimal extremum in the presence of multiple local extrema in a gradient complex environment. For this, an adaptive-extremum seeking control (adaptive-ESC) algorithm has been proposed. Agents are navigated to the vicinity of the source based on an estimated gradient using adaptive-ESC. In the proposed algorithm, both the integral gain and the amplitude of the perturbation signal are adjusted adaptively. The local convergence of the algorithm has been proved using averaging theory. The performance of the proposed algorithm is validated through simulations by employing a multi-agent system.