Finite-Time Synchronization of PDT Switched Stochastic Neural Networks under Event-Triggered Mechanism

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Bo Liu, Yong Chen, Longsuo Li
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引用次数: 0

Abstract

This paper investigates the finite-time synchronization problem of master-slave stochastic neural network systems with switching signals. First, to improve resource utilization, an event-triggered mechanism is introduced, taking into account the transmission delay in the communication process, and a master-slave synchronization error system is established. Second, to overcome the limitations of traditional switching signals, a more versatile persistent dwell-time switching rule is adopted. By constructing appropriate Lyapunov–Krasovskii functionals combined with free-weight matrix methodology, sufficient conditions for the finite-time $$ {\mathscr{H}}_{\infty } $$ synchronization of the master-slave system are derived. Based on these, the controller expression is obtained via the singular value decomposition lemma. Finally, the effectiveness of the proposed method is verified through simulation examples.

事件触发机制下PDT切换随机神经网络的有限时间同步
研究了具有切换信号的主从随机神经网络系统的有限时间同步问题。首先,为了提高资源利用率,引入事件触发机制,考虑通信过程中的传输延迟,建立主从同步错误系统;其次,为了克服传统开关信号的局限性,采用了一种更通用的持久驻留时间开关规则。通过构造适当的Lyapunov-Krasovskii泛函,结合自由权矩阵方法,导出了主从系统有限时间h∞$$ {\mathscr{H}}_{\infty } $$同步的充分条件。在此基础上,利用奇异值分解引理得到控制器表达式。最后,通过仿真算例验证了所提方法的有效性。
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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