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Ton Duc Thang University (TDTU) was established on September 24, 1997, as a public university under the Vietnam General Confederation of Labor. After 29 years of development, TDTU has grown into one of the leading universities in Vietnam, with a strong commitment to academic excellence, scientific research, innovation, and international cooperation. With modern facilities, advanced educational programs, and a multidisciplinary approach, TDTU provides a dynamic learning and research environment that promotes creativity and supports the comprehensive development of learners.

Currently, TDTU comprises 16 faculties and offers 52 undergraduate study programs, with a community of more than 77,000 alumni. The University also collaborates with more than 200 adjunct professors and researchers and has produced over 14,200 international publications, reflecting its growing contribution to global academic and scientific communities.

With the vision of becoming a world-class university, TDTU continues to strengthen its educational and research capacity, foster innovation, and enhance international collaboration. The establishment and development of the Journal of Advanced Engineering and Computation (JAEC) represent one of TDTU’s efforts to promote scientific research, disseminate advanced knowledge, and contribute to the development of engineering, technological and interdisciplinary research. More

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Vo Hoang Duy
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  • Vol 1, No 1 (2017)
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Adaptive MIMO Controller Design for Chaos Synchronization in Coupled Josephson Junctions via Fuzzy Neural Networks

Thien Bao Tat Nguyen

Abstract


In this paper, we have discussed the synchronization between coupled Josephson Junctions which experience different chaotic oscillations. Due to potential high-frequency applications, the shunted nonlinear resistive-capacitive-inductance junction (RCLSJ) model of Josephson junction was considered in this paper. In order to obtain the synchronization, an adaptive MIMO controller is developed to drive the states of the slave chaotic junction to follow the states of the master chaotic junction. The developed controller has two parts: the fuzzy neural controller and the sliding mode controller. The fuzzy neural controller employs a fuzzy neural network to simulate the behavior of the ideal feedback linearization controller, while the sliding mode controller is used to ensure the robustness of the controlled system and reduce the undesired effects of the estimate errors. In addition, the Lyapunov candidate function is also given for further stability analysis. The numerical simulations are carried out to verify the validity of the proposed control approach.


Creative Commons License
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Keywords


Chaos Synchronization, Chaotic Systems, Fuzzy Neural Networks, Josephson Junction

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DOI: http://dx.doi.org/10.25073/jaec.201711.52

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Copyright (c) 2017 Journal of Advanced Engineering and Computation



Owner: Ton Duc Thang University. All rights reserved.
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