Adaptive Fuzzy Controller for Chaos Suppression in Nonlinear Fractional Order Systems

This paper introduces a novel method for controlling a class of nonlinear non-affine systems with fractional-order dynamics, using an adaptive fuzzy technique. By incorporating a novel fractional update law in the design procedure, the controller can effectively suppress chaotic behaviour and smoothly track desired trajectories. The proposed method offers key advantages such as robustness against uncertainties, fast error convergence to the neighbourhood of zero, and satisfactory disturbance rejection performance. To demonstrate the capabilities of the proposed fractional controller, simulation results were conducted using Python on a fractional order Arneodo chaotic system. The results highlight the effectiveness and potential of the proposed method in controlling fractional-order systems.

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Publication Details

Journal
ICCK Transactions on Advanced Computing and Systems
Published
2024-12-26
DOI
https://doi.org/10.62762/tacs.2024.318686
Citations
1
Primary Topic
Chaos control and synchronization
Type
article
Field-Weighted Citation Impact
0.28
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article

Adaptive Fuzzy Controller for Chaos Suppression in Nonlinear Fractional Order Systems

Mohammad Jafar Mokarram, Inam Ullah, Islam Md Monirul, Amin Sharafian
1 citations
ICCK Transactions on Advanced Computing and Systems
Chaos control and synchronization
0.28
article

Adaptive Fuzzy Controller for Chaos Suppression in Nonlinear Fractional Order Systems

Mohammad Jafar Mokarram, Inam Ullah, Islam Md Monirul, Amin Sharafian
article en
1 citations

Abstract

This paper introduces a novel method for controlling a class of nonlinear non-affine systems with fractional-order dynamics, using an adaptive fuzzy technique. By incorporating a novel fractional update law in the design procedure, the controller can effectively suppress chaotic behaviour and smoothly track desired trajectories. The proposed method offers key advantages such as robustness against uncertainties, fast error convergence to the neighbourhood of zero, and satisfactory disturbance rejection performance. To demonstrate the capabilities of the proposed fractional controller, simulation results were conducted using Python on a fractional order Arneodo chaotic system. The results highlight the effectiveness and potential of the proposed method in controlling fractional-order systems.

ICCK Transactions on Advanced Computing and SystemsVol. 1(1)
Gachon University (KR), Shenzhen University (CN)
Openalex Percentile: Top 41%
Chaos control and synchronization
0.28
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