부산대학교 도서관

Uncertainty and delay are common phenomena in chaotic systems, but their existence will increase thedifficulty of synchronization. For the sake of actualizing synchronization of fractional order time-delay uncertainchaotic systems, we propose an adaptive fractional order fuzzy neural network synchronization scheme based onthe linear matrix inequalities. A fractional order radial basis functions neural network is applied to approximateuncertainties. According to the output of the neural network, we design a general adaptive controller for fractionalorder time-delay uncertain chaotic systems with different topological structure. Furthermore, we propose an adaptivefractional order fuzzy neural network by introducing fuzzy rules into the network. Then the fractional orderextension of the Lyapunov direct method is utilized to demonstrate the stability of the error systems under theadaptive controller. Finally, numerical simulations are conducted to verify the effectiveness of the conclusions.
Uncertainty and delay are common phenomena in chaotic systems, but their existence will increase thedifficulty of synchronization. For the sake of actualizing synchronization of fractional order time-delay uncertainchaotic systems, we propose an adaptive fractional order fuzzy neural network synchronization scheme based onthe linear matrix inequalities. A fractional order radial basis functions neural network is applied to approximateuncertainties. According to the output of the neural network, we design a general adaptive controller for fractionalorder time-delay uncertain chaotic systems with different topological structure. Furthermore, we propose an adaptivefractional order fuzzy neural network by introducing fuzzy rules into the network. Then the fractional orderextension of the Lyapunov direct method is utilized to demonstrate the stability of the error systems under theadaptive controller. Finally, numerical simulations are conducted to verify the effectiveness of the conclusions.