Event-Triggered Synchronization Control for Markov Jump Neural Networks With Partially Unknown Transition Probabilities

作     者：Fan, Cheng Su, Lei Wang, Kang Fei, Xihong 

作者机构：Anhui Univ Technol Sch Elect & Informat Engn Maanshan Peoples R China Huangshan Special Equipment Supervis & Inspect Ctr Huangshan Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL》 (Int J Robust Nonlinear Control)

年 卷 期：2025年第35卷第6期

页      面：2091-2100页

核心收录：

学科分类：0711[理学-系统科学] 0808[工学-电气工程] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0701[理学-数学] 071101[理学-系统理论] 

基　　金：Key Project of Natural Science Research in Universities of Anhui Province 

主　　题：event-triggered mechanism Neural networks synchronization control transition probabilities 

摘      要：This article studies the problem of static output feedback synchronization control of Markov jump neural networks. Given the randomness of the neural network topology and the limitations in acquiring transition probabilities, a Markov model with partially unknown transition probabilities is adopted, which aligns more closely with practical applications. To enhance communication efficiency in resource-constrained environments, an event-triggered mechanism is introduced. Additionally, in contrast to previous studies, this article employs the technique of free-weighting matrix to address the decoupling issue in such neural networks, significantly reducing the conservativeness of the static output feedback control strategy. Finally, the theoretical findings are validated through simulation, demonstrating the practical applicability and effectiveness of the theoretical results.