Distributed Global Leader-Following Coordination of MASs with Heterogeneous Input Saturation: Scheduling Low-Gain Revisited

Abstract

In this paper, we revisit the global coordinated tracking problem of the leader-following multi-agent systems with input saturation via the scheduling low-gain feedback technique, aiming to make breakthroughs from aspects such as the heterogeneity of saturation level and the distributed characteristic of scheduled tuning algorithms on the low-gain parameters, that is the newly proposed distributed scheduling low-gain approach. First, we provide a continuous-time tuning algorithm for the low-gain parameter of each follower to articulate the fundamental idea of the distributed scheduling low-gain technique on addressing heterogeneous saturation, so as to solve the global consensus tracking of multi-agent systems with heterogeneous input saturation and one leader. Then, this result is extended to the global containment tracking of multi-agent systems with multiple leaders. Furthermore, from the perspective of reducing communication burden, we further propose a distributed scheduling low-gain parameter algorithm by using the sampled relative information between each follower and its neighbors, and offer the upper and lower bounds on the sampling period to ensure the achievement of global coordination tracking. Finally, numerical simulations are performed to verify the theoretical results.