Dario Bauso

TL;DR: It is proved that such objectives can be chosen so that rational agents have a unique optimal protocol, and asymptotical consensus can be reached when the communication links between nearby agents define a time-invariant undirected network.

TL;DR: This paper provides a mean-field game that guarantees desynchronization of the agents thus improving the power network resilience and shows that the equilibrium is stable in the sense that all agents’ states converge to the equilibrium value or remain confined within a given interval for an opportune initial distribution.

TL;DR: This work considers stationary consensus protocols for networks of dynamic agents and introduces as a solution a dead-zone policy that is known as the lazy rule, where the states are required to converge in a target set of radius $\epsilon$ asymptotically or in finite time.

TL;DR: In this article, the problem of identifying a nonlinear plant by parameterizing its dynamics as a linear parameter varying (LPV) model is formulated as a problem of output regulation at various set points (stable and unstable) of the system under inputs and states constraints.

TL;DR: The main contribution of this paper is to prove in a constructive way that a gradient-descent coordination control law designed for single integrators can be easily modified to adapt for various motion constraints such as nonholonomic dynamics, linear/angular velocity saturation, and other path constraints while preserving the convergence of the entire multiagent system.