Adaptive fuzzy prescribed settling time consensus control for multi-agent systems with input hysteresis via dynamic event-triggered mechanism

An adaptive fuzzy prescribed settling time consensus control is proposed based on the dynamic event-triggered mechanism for a class of uncertain nonlinear multi-agent systems (UNMASs) subject to input hysteresis. In practical systems, the plant inevitably suffers from input hys-teresis and unknown nonlinear characteristics, which dramatically deteriorate its performance. Therefore, to eliminate the effects of those constraints, an adaptive fuzzy prescribed settling time control scheme is constructed by applying backstepping technique and first-order filter. Wherein each agent needs to be equipped with only one adaptive law for fuzzy-logic-system approximation, reducing the computational burden. Simultaneously, the synchronization error is mapped using a transformation function to achieve prescribed settling time consensus control. Moreover, a dynamic event-triggered mechanism is employed to reduce unnecessary communi-cation transmission and save energy. With the presented method, all agents synchronize to the virtual leader within a prescribed settling time. Theoretical analysis and simulation examples verify the presented method.