Enforcing Spatiotemporal Constraints in Control of Multiagent Systems with Uncertainties

We study the problem of enforcing spatial and temporal (spatiotemporal) constraints in control of multiagent systems with uncertainties. We present a new distributed control algorithm for achieving both i) a user-defined system performance by limiting the worst-case difference between the agent state trajectories and their corresponding reference state trajectories (spatial constraint) and ii) a user-defined finite-time convergence (temporal constraint). Specifically, the presented algorithm effectively addresses these spatiotemporal constraints without the need for a strict knowledge of agent uncertainties upper bounds and without relying on agent initial conditions. The efficacy of the proposed distributed control algorithm is further illustrated in a numerical example.