NDLI: Resilient state estimation for time-varying uncertain dynamical networks with data packet dropouts and switching topology: an event-triggered method

Content Provider	IET Digital Library
Author	Gao, Ming Hu, Jun Chen, Dongyan Jia, Chaoqing
Abstract	In this study, the recursive state estimation method based on the event-triggered protocol is given for time-varying uncertain complex networks with switching topology (ST), data packet dropouts (DPDs), and randomly occurring non-linearities (RONs). The event-triggered strategy is given to regulate the communications and then save the limited network resources when the measurement information is transmitted. The phenomena of RONs, ST, and DPDs are depicted by some random variables obeying the Bernoulli distribution. Besides, the estimator gain perturbations are dealt with. The major aim of this study is to present a new state estimation algorithm for addressed time-varying uncertain complex networks such that, for all STs, DPDs, and RONs, a minimal upper bound of state estimation error covariance matrix is derived by designing an optimal estimator gain matrix. Finally, a numerical simulation is presented to show the effectiveness of the provided time-varying state estimation method.
Starting Page	367
Ending Page	377
Page Count	11
ISSN	17518644
Volume Number	14
e-ISSN	17518652
Issue Number	Issue 3, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/14/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2019.0721
Journal	IET Control Theory & Applications
Publisher Date	2019-10-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Addressed Time-varying Uncertain Complex Network Algebra Complex Network Control System Analysis Covariance Matrices Data Packet Dropouts Discrete Control System Discrete Time System DPDs Estimator Gain Perturbations Event-triggered Method Event-triggered Protocol Event-triggered Strategy Matrix Algebra Modelling And Identification Network ReSource Nonlinear Control System Nonlinearities Optimal Estimator Gain Matrix Provided Time-varying State Estimation Method Random Variables Recursive State Estimation Method Resilient State Estimation RONs Simulation Stability in Control Theory State Estimation State Estimation Algorithm State Estimation Error Covariance Matrix Statistics Switching Topology Synthesis Method Time Varying Control System Time Varying System Time-varying Uncertain Dynamical Network Uncertain System
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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