Dynamic Event-triggered State Estimation for Nonlinear Coupled Output Complex Networks Subject to Innovation Constraints

被引:76
作者
Hu, Jun [1 ,2 ]
Jia, Chaoqing [1 ]
Yu, Hui [1 ]
Liu, Hongjian [3 ]
机构
[1] Harbin Univ Sci & Technol, Dept Appl Math, Harbin 150080, Peoples R China
[2] Harbin Univ Sci & Technol, Sch Automat, Harbin 150080, Peoples R China
[3] Anhui Polytech Univ, Sch Math & Phys, Wuhu 241000, Peoples R China
基金
黑龙江省自然科学基金; 中国国家自然科学基金;
关键词
Communication mechanisms - Coupling dynamics - Dynamic events - Estimation problem - Event-triggered - Network communications - Output coupling - Recursive state estimation - Saturation function - State estimation methods;
D O I
10.1109/JAS.2022.105581
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 letter investigates the recursive state estimation (RSE) problem for a class of coupled output complex networks via the dynamic event-triggered communication mechanism (DETCM) and innovation constraints (ICs). Firstly, a DETCM is employed to regulate the transmission sequences. Then, in order to improve the reliability of network communication, a saturation function is introduced to constrain the measurement outliers. A new RSE method is provided such that, for all output coupling, DETCM and ICs, an upper bound of state estimation error covariance (SEEC) is presented in a recursive form, whose trace can be minimized via parameterizing the state estimator gain matrix (SEGM). Moreover, the theoretical analysis is given to guarantee that the error dynamic is uniformly bounded. Finally, a simulation example is illustrated to show the effectiveness of the proposed RSE method. © 2014 Chinese Association of Automation.
引用
收藏
页码:941 / 944
页数:4
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