Neural network-based synchronization of uncertain chaotic systems with unknown states. Issue 4 (May 2016)

• Record Type: Journal Article
• Authors: Bagheri, P.; Shahrokhi, M.
• Is Part Of: Neural computing & applications. Volume 27:Issue 4(2016)
• Page Start: 945
• Page End: 952
• Publication Date: 2016-05
• Subjects: Chaos synchronization -- Adaptive control -- Adaptive observer -- Neural network; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-1911-2
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract In this paper, synchronization of chaotic systems with unknown parameters and unmeasured states is investigated. Two nonidentical chaotic systems in the framework of a master and a slave are considered for synchronization. It is assumed that both systems have uncertain dynamics, and states of the slave system are not measured. To tackle this challenging synchronization problem, a novel neural network-based adaptive observer and an adaptive controller have been designed. Moreover, a neural network is utilized to approximate the unknown dynamics of the slave system. The proposed method imposes neither restrictive assumption nor constraint on the dynamics of the systems. Furthermore, the stability of the entire closed-loop system in the presence of the observer dynamics has been established. Finally, effectiveness of the proposed scheme is demonstrated via computer simulation.