Predefined-time quasi-synchronization for stochastic T-S fuzzy complex networks via intermittent self-triggered control

This paper studies the predefined-time quasi-synchronization of stochastic Takagi-Sugeno fuzzy complex networks (ST-SFCNs) under aperiodic intermittent self-triggered control (AIS-TC). Unlike fixed/finite-time synchronization approaches, we introduce a time-varying function with adjustable gains, enabling the network states to achieve synchronization within a predefined time while ensuring that the bounds remain controllable. An aperiodic intermittent event-triggered control (AIE-TC) scheme with continuous state monitoring is first developed, which is subsequently transformed into an improved AIS-TC mechanism. The proposed AIS-TC strategy eliminates Zeno phenomena without requiring continuous state measurement or mathematical expectation. Notably, the developed AIS-TC scheme can reduce controller updates and demonstrates enhanced flexibility with less conservative implementation conditions through an average control rate mechanism. Finally, the algorithm is applied to a simulation example of an islanded microgrid to verify its feasibility.