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Fixed-time Synchronization of Fractional Order Memristive MAM Neural Networks by Sliding Mode Control
Neurocomputing ( IF 6 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.neucom.2020.03.043
Weiping Wang , Xiao Jia , Zhen Wang , Xiong Luo , Lixiang Li , Jürgen Kurths , Manman Yuan

Abstract In this paper, we first established the fractional order memristive multidirectional associative memory neural networks (FMMAMNNs) model, and then considered its fixed-time synchronization control problem. On the basis of sliding model control and Lyapunov stability theorem, a fractional order sliding mode controller is constructed. By adding this controller to the response system, the error of the driver-response systems gradually converges to 0 in a fixed time. Compared with the previous researches, this paper considers a more complex model, and the proposed control theories can ensure that the setting time is only related to the model and controller, but not to the initial states of the system. Besides, the control theories are also applicable to the integer order models. Finally, two numerical simulations are given, the results show the validity of the theories.

中文翻译:

通过滑模控制实现分数阶忆阻 MAM 神经网络的固定时间同步

摘要 在本文中,我们首先建立了分数阶忆阻多向关联记忆神经网络(FMMAMNNs)模型,然后考虑了其固定时间同步控制问题。在滑模控制和李雅普诺夫稳定性定理的基础上,构造了分数阶滑模控制器。通过将该控制器加入到响应系统中,驾驶员响应系统的误差在固定时间内逐渐收敛到 0。与以往的研究相比,本文考虑了一个更复杂的模型,所提出的控制理论可以保证整定时间只与模型和控制器有关,而与系统的初始状态无关。此外,控制理论也适用于整数阶模型。最后给出了两个数值模拟,
更新日期:2020-08-01
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