Event-triggered H∞ synchronization for switched discrete time delayed recurrent neural networks with actuator constraints and nonlinear perturbations. Issue 7 (May 2020)
- Record Type:
- Journal Article
- Title:
- Event-triggered H∞ synchronization for switched discrete time delayed recurrent neural networks with actuator constraints and nonlinear perturbations. Issue 7 (May 2020)
- Main Title:
- Event-triggered H∞ synchronization for switched discrete time delayed recurrent neural networks with actuator constraints and nonlinear perturbations
- Authors:
- Vadivel, R.
Syed Ali, M.
Hoon Joo, Young - Abstract:
- Abstract: In this paper, event-triggered H ∞ synchronization problem is investigated for robust discrete time delayed recurrent neural networks with switching parameters, actuator constraints and non-linear perturbations. An event-triggered communication transmission scheme is adopted and an event generator is presented between the controller and sensor. Meanwhile, average dwell time approach together with the unreliable communication links are considered between the switched recurrent neural networks. Our aim is to design a controller such that, the unavoidable phenomenon of network-induced delays is fully considered, the resulting closed-loop system is exponentially stable with the disturbance attenuation level γ ^ > 0 . By utilizing techniques like improved summation inequality together with Jensen's inequality and Lyapunov- Krasovskii functional, results are derived and formulated in terms of linear matrix inequalities (LMIs) which can be easily verified by the MATLAB LMI control toolbox. Finally, numerical examples are given to demonstrate the effectiveness and benefits of the developed stability criteria.
- Is Part Of:
- Journal of the Franklin Institute. Volume 357:Issue 7(2020)
- Journal:
- Journal of the Franklin Institute
- Issue:
- Volume 357:Issue 7(2020)
- Issue Display:
- Volume 357, Issue 7 (2020)
- Year:
- 2020
- Volume:
- 357
- Issue:
- 7
- Issue Sort Value:
- 2020-0357-0007-0000
- Page Start:
- 4079
- Page End:
- 4108
- Publication Date:
- 2020-05
- 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.2020.01.016 ↗
- 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
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13392.xml