Distributed data-driven optimal synchronisation of multi-agent systems with input saturation

This paper discusses the optimal synchronisation problem of multi-agent systems with unknown system dynamics, where each agent is subject to both input saturation and external disturbances. A novel data-driven control approach is developed in this paper based on low-gain technique, output regulation, differential game theory, and adaptive dynamic programming (ADP). Unlike existing approaches to the data-driven optimal synchronisation problem, our method eliminates the need for an initially admissible stabilising control policy, and the proposed distributed control law ensures asymptotic tracking even in the presence of both modelling disturbances and unmodeled disturbances.