Zero-Error Consensus Tracking With Preassignable Convergence for Nonaffine Multiagent Systems.

In this paper, we investigate the consensus tracking control problem for networked multiagent systems (MASs) with unknown nonaffine dynamics. Our goal is to achieve asymptotic (rather than ultimately uniformly bounded) consensus tracking, which is quite challenging especially if nonvanishing/nonparametric uncertainties are involved and at the same time the control protocol is required to be fully distributed and continuous everywhere. Here, we present a conceptually new and structurally simple solution with distributed and continuous control action. The developed method is capable of ensuring zero-error tracking with a unique converging feature in that the consensus tracking error first converges to a small adjustable residual set around zero within a prescribed finite time, and then further shrinks to zero exponentially. The key technique lies in the utilization of a state transformation based on certain scaling function. Our method also prevents the restrictive requirement that all subsystems have access to the linearly parameterized information as imposed in most existing consensus tracking results for nonlinear MAS.