兰州理工大学学报 ›› 2026, Vol. 52 ›› Issue (2): 70-78.

• 自动化技术与计算机技术 • 上一篇    下一篇

基于通信协议的网络化系统抗野值最终有界滤波

王志文*1,2,3, 郝梦璐1, 张磐1   

  1. 1.兰州理工大学 自动化与电气工程学院, 甘肃 兰州 730050;
    2.兰州理工大学 甘肃省工业过程先进控制重点实验室, 甘肃 兰州 730050;
    3.兰州理工大学 电气与控制工程国家级实验教学示范中心, 甘肃 兰州 730050
  • 收稿日期:2024-01-09 出版日期:2026-04-28 发布日期:2026-04-28
  • 通讯作者: 王志文(1976-),男,甘肃民勤人,博士,教授,博导. Email:wzw@lut.edu.cn
  • 基金资助:
    国家自然科学基金(62363024,62263019),甘肃省科技重大专项(21ZD4GA028)

The outlier-resistant ultimately bounded filtering for networked systems with communication protocol

WANG Zhi-wen1,2,3, HAO Meng-lu1, ZHANG Pan1   

  1. 1. School of Automation and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
    2. Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China;
    3. National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China
  • Received:2024-01-09 Online:2026-04-28 Published:2026-04-28

摘要: 针对具有随机通信协议非线性离散系统研究了抗野值的最终有界滤波问题.首先,为了避免数据拥塞,在此引入随机通信协议来合理调度传感器节点的数据传输.此外,设计了一种具有自适应饱和阈值的滤波器结构来抑制量测野值对滤波性能的影响.在此框架下,针对非线性离散系统,建立了抗野值和随机通信协议传输机制的动态滤波误差系统模型.在此模型的基础上,构造合适的Lyapunov函数并利用线性矩阵不等式技术,得到了动态滤波误差系统最终有界的充分条件.随后,通过求解一个最优化问题,获得具有满意滤波性能的滤波器增益矩阵.最后,通过仿真验证了所提出的自适应抗野值滤波算法的有效性和优越性.

关键词: 网络化控制系统, 最终有界滤波, 测量野值, 随机通信协议

Abstract: The problem of outlier-resistant ultimately bounded filtering for nonlinear discrete systems under a stochastic communication protocol is investigated. First of all, the stochastic communication protocol is introduced to rationally schedule data transmission of sensor nodes to mitigate data congestion. In addition, the filter structure with an adaptive saturation threshold is designed to suppress the influence of measurement outliers on the filtering performance. On this basis, the dynamic filtering error system model is established that accounts for both outlier-resistant mechanism and the stochastic communication protocol mechanism in nonlinear discrete systems. Subsequently, the sufficient condition for the ultimate boundedness of the dynamic filtering error system is obtained by establishing a suitable Lyapunov function and utilizing the linear matrix inequality technique. Furthermore, the filtering gain matrices with satisfactory filtering performance are obtained by solving an optimization problem. Finally, the effectiveness and superiority of the proposed adaptive outlier-resistant filtering algorithm are verified by simulation.

Key words: networked control systems, ultimately bounded filtering, measurement outliers, stochastic communication protocol

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