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

Distributed Adaptive Consensus Control of High Order Unknown Nonlinear Networked Systems with Guaranteed Performance