Distributed Recursive State Estimation for a Class of Multi-Rate Nonlinear Systems Over Wireless Sensor Networks Under FlexRay Protocols

被引:14
|
作者
Shen, Yuxuan [1 ,2 ,3 ]
Wang, Zidong [4 ]
Dong, Hongli [1 ,2 ,3 ]
Lu, Guoping [5 ]
Alsaadi, Fawaz E. [6 ,7 ]
机构
[1] Northeast Petr Univ, Artificial Intelligence Energy Res Inst, Daqing 163318, Peoples R China
[2] Northeast Petr Univ, Heilongjiang Prov Key Lab Networking & Intelligent, Daqing 163318, Peoples R China
[3] Northeast Petroleum Univ, Sanya Offshore Oil & Gas Res Inst, Sanya 572024, Peoples R China
[4] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, England
[5] Nantong Univ, Sch Elect Engn, Nantong 226019, Peoples R China
[6] King Abdulaziz Univ, Dept Informat Technol, Jeddah 21589, Saudi Arabia
[7] King Abdulaziz Univ, Fac Comp & Informat Technol, Jeddah 21589, Saudi Arabia
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2023年 / 10卷 / 03期
基金
中国国家自然科学基金; 黑龙江省自然科学基金;
关键词
Protocols; State estimation; Wireless sensor networks; Dynamic scheduling; Job shop scheduling; Vehicle dynamics; Robot sensing systems; Distributed state estimation; FlexRay protocol; multi-rate nonlinear systems; sensor networks; uniform boundedness; STOCHASTIC NONLINEARITIES; NEURAL-NETWORKS; FUSION; SUBJECT; CHANNEL;
D O I
10.1109/TNSE.2022.3229889
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper is concerned with the distributed recursive state estimation problem for a class of multi-rate nonlinear systems over the sensor networks. The sensor nodes in the sensor network are communicated with each other through communication networks equipped with the FlexRay protocol, which is a hybrid protocol consists of both static and dynamic scheduling rules regulated by two time-varying variables within a communication cycle. The main purpose of this paper is to design local distributed state estimators by taking into account the scheduling of the FlexRay protocol. Upper bounds are first obtained on the local state estimation error covariances (EECs) by solving two matrix recursive equations, and then the minimum of the derived upper bounds are acquired through calculating adequate local gain matrices. Finally, the local estimates are fused by using the covariance intersection fusion method. Moreover, the uniform boundedness of the upper bounds on local EECs are analyzed. An illustrate example is provided to verify the effectiveness of the proposed distributed state estimation algorithm.
引用
收藏
页码:1551 / 1563
页数:13
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