Event-Based Adaptive Fuzzy Constrained Control for Nonlinear Multiagent Systems via State-Error Unified Barrier Function Approach

This article investigates the problem of adaptive fuzzy consensus control for a class of interconnected nonlinear multiagent systems. To effectively address the dual requirement of full-state constraints and prescribed performance, we propose a novel unified barrier function that effectively constrains the states and errors separately. This approach eliminates the need for tedious computations, allowing for direct presetting of state and error bounds. The concept of “bridge hole” is introduced, referring to the states' transition from unconstrained to constrained and back to unconstrained. The control method demonstrates the capability to handle multiple bridges, with the number of bridges being able to be ${\bm {n}}$ or 0. Furthermore, event-triggered mechanisms are also considered among neighbors and the internal event-triggered mechanism in the actuator-to-controller channel, with the aim of minimizing the communication burden. Finally, some simulation results are provided to validate the effectiveness of the approach.