Back to Search
Start Over
Dynamic event-triggered [formula omitted] state estimation for delayed complex networks with randomly occurring nonlinearities.
- Source :
-
Neurocomputing . Jan2021, Vol. 421, p97-104. 8p. - Publication Year :
- 2021
-
Abstract
- This paper aims to iron out the dynamic event-triggered (ET) H ∞ state estimation issue for a class of discrete time-delay complex networks (CNs) with randomly occurring nonlinearities (RONs). In the signal transmission among the nodes, the effect of time-varying delays is examined. The RONs under consideration is modelled by a series of random variables obeying Bernoulli distribution. In the design of state estimators, a dynamic ET scheme is utilized with the hope of improving the energy utilization efficiency. A sufficient condition is first derived to ensure the exponential mean-square (EMS) stability and H ∞ performance index of the estimation error systems. Then, by using the matrix inequality technology, the desired state estimators are designed. Lastly, a numerical simulation example is given to show the usefulness of the proposed estimator design algorithm. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 421
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 147114394
- Full Text :
- https://doi.org/10.1016/j.neucom.2020.08.048