Neural network synchronization of fractional-order chaotic systems subject to backlash nonlinearity
Source abstract
Abstract
This paper investigates the neural network (NN) synchronization controller design problem of fractional-order chaotic systems (FOCSs) subject to disturbances and backlash-like hysteresis input. First, we divide the backlash-like hysteresis input into two parts, one of which is the actual controller and the other that can be approximated by NNs. Then, an adaptive NN synchronization control input is implemented to drive the synchronization error between two identical FOCSs into a small domain. Finally, the effect of our approach is indicated by simulation results.
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Research context
OpenAlex topics: Chaos control and synchronization · Neural Networks and Applications · Neural Networks Stability and Synchronization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematics and Physics, Guangxi University for Nationalities 1 , Nanning 530006, China
Department of Applied Mathematics, Huainan Normal University 2 , Huainan 232038, China
Funding
Natural Science Foundation of Huainan Normal University · Middle-Aged and Young Teachers’ Basic Ability Promotion Project of Guangxi
References (37)
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