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A novel adaptive interval type-3 neuro-fuzzy robust controller for nonlinear complex dynamical systems with inherent uncertainties

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Abstract

A novel observer-based control policy based on an interval type-3 fuzzy logic system is developed to tackle the main limitations of fuzzy-based controllers in sense of approximation of uncertainties and analyzing nonlinear complex systems without detailed dynamics model information. For this purpose, a novel scheme is proposed that includes online optimized tuning rules, a simple type reduction method, and adaptive mechanisms. Also, an adaptive compensator is implemented to enhance the robust performance of the closed-loop system and reduce the effect of approximation errors. For the stability analysis, appropriate Lyapunov functions and Barbalat’s lemma are employed. By both simulations and experimentally implementation, it is shown that the suggested approach results in a more accurate approximation of unknown models and complicated nonlinearities, and good resistance against uncertainties and parameter variations.

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Abbreviations

IT3FLS:

Interval type-3 fuzzy logic system

SM:

Sliding mode

TS:

Takagi-Sugeno

IT2FLS:

Interval type-2 fuzzy logic system

T1FLS:

Type-1 fuzzy logic system

T2F:

Type-2 fuzzy

PI:

Proportional–Integral

FS:

Fuzzy set

MPU6050:

Angle acceleration sensor

PCB:

Printed circuit board

GFSK:

Gaussian frequency shift keying

MF:

Membership function

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Acknowledgements

This research is financially supported by the Ministry of Science and Technology of China (Grant No. 2019YFE0112400) and the Department of Science and Technology of Shandong Province (Grant No. 2021CXGC011204).

Funding

This research is financially supported by the Ministry of Science and Technology of China (Grant No.2019YFE0112400) and the Department of Science and Technology of Shandong Province (Grant No. 2021CXGC011204).

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Authors and Affiliations

  1. Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang, 110870, China

    Amin Taghieh, Ardashir Mohammadzadeh & Chunwei Zhang

  2. Department of Applied Mathematics, Bharathiar University, Coimbatore, 641-046, India

    Sakthivel Rathinasamy

  3. FEMA & DLT Centre, University of Malta, Msida, MSD, 2080, Malta

    Stelios Bekiros

  4. London School of Economics (LSE), LSE Health Centre, London, WC2A2AE, UK

    Stelios Bekiros

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  1. Amin Taghieh
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  4. Sakthivel Rathinasamy
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  5. Stelios Bekiros
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Correspondence to Ardashir Mohammadzadeh or Chunwei Zhang.

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Taghieh, A., Mohammadzadeh, A., Zhang, C. et al. A novel adaptive interval type-3 neuro-fuzzy robust controller for nonlinear complex dynamical systems with inherent uncertainties. Nonlinear Dyn 111, 411–425 (2023). https://doi.org/10.1007/s11071-022-07867-9

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