Observer-based sliding mode control for synchronization of delayed chaotic neural networks with unknown disturbance.
作者： Yongshun Zhao , Xiaodi Li , Peiyong Duan
DOI: 10.1016/J.NEUNET.2019.05.013
关键词: Observer (quantum physics) 、 Chaotic neural network 、 Sliding mode control 、 Synchronization 、 Linear matrix inequality 、 Surface (mathematics) 、 Computer science 、 Control theory 、 Disturbance (geology) 、 Structure (category theory)
摘要: Abstract This paper considers the synchronization of delayed chaotic neural networks with unknown disturbance via observer-based sliding mode control. We design a surface involving integral structure and discontinuous control law such that trajectories error system converge to in finite time remain on it thereafter. Then, by constructing Lyapunov–Krasovskii functional using linear matrix inequality (LMI) technique, some sufficient conditions are derived guarantee networks. The advantages our proposed results include:(i) It can be applied synchronous for drive response systems different structures; (ii) disturbance. Finally, simulation example is shown illustrate methods.
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