Event-triggered H∞ state estimation for state-saturated complex networks subject to quantization effects and distributed delays. Issue 5 (March 2018)
- Record Type:
- Journal Article
- Title:
- Event-triggered H∞ state estimation for state-saturated complex networks subject to quantization effects and distributed delays. Issue 5 (March 2018)
- Main Title:
- Event-triggered H∞ state estimation for state-saturated complex networks subject to quantization effects and distributed delays
- Authors:
- Li, Qi
Shen, Bo
Wang, Zidong
Alsaadi, Fuad E. - Abstract:
- Abstract: This paper is concerned with the event-triggered H ∞ state estimation problem for a class of discrete-time complex networks subject to state saturations, quantization effects as well as randomly occurring distributed delays. A series of Bernoulli distributed random variables is utilized to model the random occurrence of distributed delays. For the energy-saving purpose, an event-triggered mechanism is proposed to decide whether the current quantized measurement should be transmitted to the estimator or not. For the state-saturated complex networks, our aim is to design event-triggered state estimators that guarantee both the exponential mean-square stability of and the H ∞ performance constraint on the error dynamics of the state estimation. Stochastic analysis is conducted, in combination with the Lyapunov functional approach, to derive sufficient conditions for the existence of the desired estimators whose gain matrices are obtained by solving a set of matrix inequalities. An illustrative example is exploited to show the usefulness of the estimator design algorithm proposed.
- Is Part Of:
- Journal of the Franklin Institute. Volume 355:Issue 5(2018)
- Journal:
- Journal of the Franklin Institute
- Issue:
- Volume 355:Issue 5(2018)
- Issue Display:
- Volume 355, Issue 5 (2018)
- Year:
- 2018
- Volume:
- 355
- Issue:
- 5
- Issue Sort Value:
- 2018-0355-0005-0000
- Page Start:
- 2874
- Page End:
- 2891
- Publication Date:
- 2018-03
- Subjects:
- Science -- Periodicals
Technology -- Periodicals
Patents -- United States -- Periodicals
505 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/00160032 ↗ - DOI:
- 10.1016/j.jfranklin.2018.01.020 ↗
- Languages:
- English
- ISSNs:
- 0016-0032
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4755.000000
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