  Adaptive cooperative tracking control with prescribed performance function
(PPF) is proposed for high-order nonlinear multi-agent systems. The tracking
error originally within a known large set is confined to a smaller predefined
set using this approach. Using output error transformation, the constrained
system is relaxed and mapped to an unconstrained one. The controller is
conceived under the assumption that the agents' nonlinear dynamics are unknown
and the perceived network is structured and strongly connected. Under the
proposed controller, all agents track the trajectory of the leader node with
guaranteed uniform ultimately bounded transformed error and bounded adaptive
estimate of unknown parameters and dynamics. In addition, the proposed
controllers with PPF are distributed such that each follower agent requires
information between its own state relative to connected neighbors. Proposed
controller is validated for robustness and smoothness using highly nonlinear
heterogeneous networked system with uncertain time-varying parameters and
external disturbances. Index Terms: Prescribed performance, neuro-adaptive,
high order, Transformed error, Multi-agents, Distributed control, Consensus,
Synchronization, Transient, Steady-state error, MIMO, SISO.
