Application of Combining Type 2 Fuzzy CMAC Network and Jordan Neural Network in Nonlinear System Control

Document Type : Research Paper

Authors

Lac Hong University

Abstract

This paper proposes a new solution for controlling complex nonlinear systems, through the combination of a type 2 fuzzy CMAC controller and Jordan neural network. This method takes advantage of type 2 fuzzy CMAC in dealing with uncertainties and learning ability, while the Jordan neural network helps to enhance the stability and improve the performance of the system. The adaptive learning laws were designed to help the proposed network automatically update the network parameters. The results from simulations and experiments have shown that this method achieves superior accuracy and robustness compared to other methods. When applied to control the Magnetic Levitation System, this method shows great potential in solving complex nonlinear control problems, opening up new approaches in this field.

Keywords

Main Subjects

References

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Iranian Journal of Fuzzy Systems
Volume 22, Issue 2
March and April 2025
Pages 25-39

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