Distributed algorithms for aggregative games with multiple uncertain Euler–Lagrange systems over switching networks

In this paper, we investigate the distributed Nash equilibrium (NE) seeking problem for aggregative games with multiple uncertain Euler–Lagrange (EL) systems over jointly connected and weight-balanced switching networks. The designed distributed controller consists of two parts: a dynamic average consensus part that asymptotically reproduces the unknown NE, and an adaptive reference-tracking module responsible for steering EL systems’ positions to track a desired trajectory. The generalized Barbalat’s Lemma is used to overcome the discontinuity of the closed-loop system caused by the switching networks. The proposed algorithm is illustrated by a sensor network deployment problem.