International Journal of Control, Automation, and Systems 2024; 22(1): 48-60
https://doi.org/10.1007/s12555-022-0381-4
© The International Journal of Control, Automation, and Systems
This paper is bound up with the distributed consensus recursive filtering subject to random nonlinear disturbances systems under round-robin (RR) protocol. In order to describe the system model more realistically, the nonlinear time delay is introduced into the system. RR protocol is used in this paper to reduce the network burden of information transmission among nodes. In the developed consensus recursive filtering algorithm, each node only uses the information of itself and neighboring nodes. The objective of the issue is to design a nonlinear filter for each node and calculate the corresponding filter gain matrix. The filter gain matrix is obtained by minimizing the upper bound. The upper bound of the filtering error covariance can be got by solving two matrix difference equations. By mathematical induction, it is proved that the filtering error covariance is convergent. In the end, several simulation pictures are shown to demonstrate the effectiveness of the designed filtering scheme.
Keywords Consensus recursive filtering, nonlinear systems, random nonlinear disturbances, round-robin protocol, sensor networks.
International Journal of Control, Automation, and Systems 2024; 22(1): 48-60
Published online January 1, 2024 https://doi.org/10.1007/s12555-022-0381-4
Copyright © The International Journal of Control, Automation, and Systems.
Long Xu*, Chang Tian, and Hui Yu
Harbin University of Science and Technology
This paper is bound up with the distributed consensus recursive filtering subject to random nonlinear disturbances systems under round-robin (RR) protocol. In order to describe the system model more realistically, the nonlinear time delay is introduced into the system. RR protocol is used in this paper to reduce the network burden of information transmission among nodes. In the developed consensus recursive filtering algorithm, each node only uses the information of itself and neighboring nodes. The objective of the issue is to design a nonlinear filter for each node and calculate the corresponding filter gain matrix. The filter gain matrix is obtained by minimizing the upper bound. The upper bound of the filtering error covariance can be got by solving two matrix difference equations. By mathematical induction, it is proved that the filtering error covariance is convergent. In the end, several simulation pictures are shown to demonstrate the effectiveness of the designed filtering scheme.
Keywords: Consensus recursive filtering, nonlinear systems, random nonlinear disturbances, round-robin protocol, sensor networks.
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