Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 发表日期：

    2026年1月12日

查看全文
  • Haoyu Zhou,
  • Yongbao Wu,
  • Jian Liu,
  • Lei Xue,
  • Changyin Sun

摘要

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.