摘要
针对离散时滞Markov跳变神经网络系统,研究异步耗散滤波器和动态事件触发器的协同优化设计问题。通过引入动态事件触发器减少数据的传输量,并采用隐Markov模型描述滤波器与原系统间的模态异步程度。在此框架下,利用李雅普诺夫泛函和耗散理论,得到使滤波误差动态系统满足随机稳定且严格耗散的充分条件,随后借助松弛矩阵技术和Projection引理,给出事件触发器和滤波器矩阵参数的求解方法,并通过数值算例仿真验证方案的有效性。
In this paper,the collaborative optimization design of asynchronous dissipative filter and dynamic event trigger is studied for discrete time-delay Markov jump neural network system.By introducing the dynamic event trigger to reduce the amount of data transmission,the modal asynchrony between the designed filter and the original system is described by a hidden Markov model.In this framework,using Lyapunov functions and dissipative theory,sufficient conditions for the filtering error dynamic system to satisfy stochastic stability and strict dissipativity are obtained.Subsequently,with the help of relaxation matrix techniques and the Projection lemma,methods for solving the matrix parameters of the event triggers and filters are further provided.Finally,the effectiveness of the proposed solution is verified through a numerical simulation example.
作者
姜明帅
刘卫俊
关聪
陈惠英
JIANG Mingshuai;LIU Weijun;GUAN Cong;CHEN Huiying(School of Engineering,Huzhou University,Huzhou 313000,China;Zhejiang Hairui Network Technology Co.,Ltd.,Huzhou 313000,China;Shenyang Xiangyuan Electric Power Engineering Co.,Ltd.,Shenyang 110102,China)
出处
《湖州师范学院学报》
2025年第4期51-61,共11页
Journal of Huzhou University
基金
浙江省公益技术研究计划工业项目(LGG21E020001)。
关键词
Markov神经网络
时滞
动态事件触发机制
异步滤波
Markov neural network
time-delay
dynamic event-triggered mechanism
asynchronous filtering
