Recursive state estimation for nonlinear coupling complex networks with time-varying topology and round-robin protocol

被引:4
|
作者
Jia, Chaoqing [1 ,2 ]
Hu, Jun [1 ,2 ,3 ]
Li, Bing [3 ]
Liu, Hongjian [4 ]
Wu, Zhihui [2 ,3 ]
机构
[1] Harbin Univ Sci & Technol, Dept Math, Harbin 150080, Peoples R China
[2] Harbin Univ Sci & Technol, Heilongjiang Prov Key Lab Optimizat Control & Inte, Harbin 150080, Peoples R China
[3] Harbin Univ Sci & Technol, Sch Automation, Harbin 150080, Peoples R China
[4] Anhui Polytech Univ, Sch Math Phys & Finance, Wuhu 241000, Peoples R China
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
UNIFORM QUANTIZATION; SYSTEMS;
D O I
10.1016/j.jfranklin.2022.05.009
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is devoted to solving the recursive state estimation (RSE) issue for a class of complex networks (CNs) with Round-Robin (RR) protocol and switching nonlinearities (SNs). A random variable obeying the Bernoulli distribution with known statistical properties is introduced to describe the switch-ing phenomenon between two nonlinear functions. A Gaussian noise and time-varying outer coupling strength are adopted to show the changeable network topology (CNT). The RR protocol is applied to regulate signal transmissions, which determines that the element in measurement output has access to the communication networks at each step. The purpose of this paper is to construct a recursive state estimator such that, for all SNs, time-varying topology and RR protocol, the expected state estimation performance is guaranteed. Specifically, based on two recursive matrix equations, the covariance upper bound (CUB) of state estimation error is obtained firstly and then minimized via designing estimator gain in a proper way. Moreover, a feasible criterion is given to guarantee that the trace of obtained CUB is bounded and a monotonicity relationship is established between state estimation error and time-varying outer coupling strength. Lastly, a simulation experiment is illustrated to verify the feasibility of the addressed estimation method.(c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:5575 / 5595
页数:21
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