Event-Triggered Adaptive Consensus Control for Nonlinear Multi-Agent Systems with Prescribed Performance and Full-State Constraints

This work addresses the output agreement problem for networked nonlinear agents with simultaneous transient performance specifications and state limitations. A performance function confines synchronization deviation of each agent within a user-designed envelope that quantifies both convergence speed and permissible steady-state offset. Logarithmic barrier certificates are embedded into the recursive control construction to prevent any state variable from exiting its admissible region. Unknown plant nonlinearities are compensated via Gaussian radial basis function approximators, and a first-order filter bypasses the repeated analytic differentiation that complicates traditional recursive designs. To reduce frequent actuator adjustments, each agent’s control signal is refreshed only at aperiodic instants governed by a local dynamic triggering rule depending exclusively on its own measurements. A Lyapunov analysis confirms that all closed-loop trajectories remain semi-globally uniformly bounded, the synchronization errors obey the imposed performance limits, the state restrictions are never breached, and infinitely many triggering attempts cannot accumulate in finite time. The theoretical findings are corroborated through a computational experiment involving four heterogeneous followers coordinated by a single virtual leader.