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Volume 11 Issue 8
Aug.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(8): 1836-1848
W. Qian, Y. Wu, and  B. Shen,  “Novel adaptive memory event-triggered-based fuzzy robust control for nonlinear networked systems via the differential evolution algorithm,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 8, pp. 1836–1848, Aug. 2024. doi: 10.1109/JAS.2024.124419
Citation: W. Qian, Y. Wu, and  B. Shen,  “Novel adaptive memory event-triggered-based fuzzy robust control for nonlinear networked systems via the differential evolution algorithm,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 8, pp. 1836–1848, Aug. 2024. doi: 10.1109/JAS.2024.124419
shu

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm

doi: 10.1109/JAS.2024.124419
Funds:  This work was partially supported by the National Natural Science Foundation of China (61973105, 62373137)
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    Abstract

  • This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2 (IT2) fuzzy technique under a differential evolution algorithm. To provide a more reasonable utilization of the constrained communication channel, a novel adaptive memory event-triggered (AMET) mechanism is developed, where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data. Sufficient conditions with less conservative design of the fuzzy imperfect premise matching (IPM) controller are presented by introducing the Wirtinger-based integral inequality, the information of membership functions (MFs) and slack matrices. Subsequently, under the IPM policy, a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 Takagi-Sugeno (T-S) fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect. Finally, simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

     

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    Highlights

    • An adaptive memory event-triggered is designed to reduce communication resource waste
    • A new method of fuzzy controller design is given based on the information of membership functions
    • An online membership functions iteration policy is proposed to get better control performance

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