一类不确定混沌供应链的混沌同步及其ANFIS控制

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Seyed Mohamad Hamidzadeh, Mohsen Rezaei, M. Ranjbar-Bourani
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引用次数: 0

摘要

本文建立了一个三层混沌供应链网络的模型。该模型考虑了制造商中零售商的不确定性。提出了一种自适应神经模糊方法来同步两个混沌供应链网络。为了训练自适应神经模糊控制器,首先设计了一种非线性反馈控制方法。然后,利用Lyapanov理论,证明了非线性反馈控制器可以在有限时间内将同步误差减小到零。仿真结果表明,所提出的神经模糊控制器结构能很好地控制两个混沌供应链网络的同步。在仿真的另一部分,对非线性控制器和自适应神经模糊控制器的性能进行了比较。并在仿真结果中对控制器信号进行了描述。这个信号表明,在现实世界中实现的成本并不高,而且很容易实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chaos synchronization for a class of uncertain chaotic supply chain and its control by ANFIS
In this paper, modelling of a three-level chaotic supply chain network. This model has the uncertainty of the retailer in the manufacturer. An adaptive neural fuzzy method has been proposed to synchronize the two chaotic supply chain networks. To train adaptive neural fuzzy controller, first, a nonlinear feedback control method is designed. Then, using Lyapanov theory, it is proved that the nonlinear feedback controller can reduce the synchronization error to zero in a finite time. The simulation results show that the proposed neural fuzzy controller architecture well controls the synchronization of the two chaotic supply chain networks. In the other part of the simulation, a comparison is made between the performance of the nonlinear controller and the adaptive neural fuzzy. Also, in the simulation results, the controller signal is depicted. This signal indicates that the cost of implementation in the real world is not high and is easily implemented.
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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