Control of Uncertain Multiagent Systems With Spatiotemporal Constraints

In this article, we propose a new distributed control algorithm for multiagent systems with single-integrator dynamics subject to spatial and temporal constraints in the presence of vanishing and nonvanishing system uncertainties. In particular, the proposed approach guarantees a user-defined performance bound on the system error signal of each agent (spatial constraints), where an error-dependent learning rate is used in the adaptive control architecture. In addition, the multiagent system achieves a prescribed finite-time convergence to the position of a time-varying leader (temporal constraint), where we make use of a time transformation approach. This time transformation links a prescribed finite-time interval to a stretched infinite-time interval, where we perform the stability analysis on the latter interval. The efficacy of the proposed control architecture is also demonstrated through a numerical example.