Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80635
Title: Rejecting chaotic disturbances using a super-exponential-zeroing neurodynamic approach for synchronization of chaotic sensor systems
Authors: Chen, D
Li, S 
Wu, Q
Keywords: Chaos
Chaotic disturbance rejection
Fast synchronization
Recurrent neural networks
Sensors
Zeroing neurodynamic
Issue Date: 2018
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Sensors (Switzerland), 2018, v. 19, no. 1, 74 How to cite?
Journal: Sensors (Switzerland) 
Abstract: Due to the existence of time-varying chaotic disturbances in complex applications, the chaotic synchronization of sensor systems becomes a tough issue in industry electronics fields. To accelerate the synchronization process of chaotic sensor systems, this paper proposes a super-exponential-zeroing neurodynamic (SEZN) approach and its associated controller. Unlike the conventional zeroing neurodynamic (CZN) approach with exponential convergence property, the controller designed by the proposed SEZN approach inherently possesses the advantage of super-exponential convergence property, which makes the synchronization process faster and more accurate. Theoretical analyses on the stability and convergence advantages in terms of both faster convergence speed and lower error bound within the task duration are rigorously presented. Moreover, three synchronization examples substantiate the validity of the SEZN approach and the related controller for synchronization of chaotic sensor systems. Comparisons with other approaches such as the CZN approach, show the convergence superiority of the proposed SEZN approach. Finally, extensive tests further investigate the impact on convergence performance by choosing different values of design parameter and initial state.
URI: http://hdl.handle.net/10397/80635
ISSN: 1424-8220
DOI: 10.3390/s19010074
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