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Volume 11 Issue 3
Mar.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(3): 723-733
X. Wan, C. Zhang, F. Wei, C.-K. Zhang, and  M. Wu,  “Hybrid dynamic variables-dependent event-triggered fuzzy model predictive control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 3, pp. 723–733, Mar. 2024. doi: 10.1109/JAS.2023.123957
Citation: X. Wan, C. Zhang, F. Wei, C.-K. Zhang, and  M. Wu,  “Hybrid dynamic variables-dependent event-triggered fuzzy model predictive control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 3, pp. 723–733, Mar. 2024. doi: 10.1109/JAS.2023.123957
shu

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

doi: 10.1109/JAS.2023.123957
Funds:  This work was supported by the National Natural Science Foundation of China (62073303, 61673356), Hubei Provincial Natural Science Foundation of China (2015CFA010), and the 111 Project (B17040)
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    Abstract

  • This article focuses on dynamic event-triggered mechanism (DETM)-based model predictive control (MPC) for T-S fuzzy systems. A hybrid dynamic variables-dependent DETM is carefully devised, which includes a multiplicative dynamic variable and an additive dynamic variable. The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem (OP). To facilitate the co-design of the MPC controller and the weighting matrix of the DETM, an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant (RPI) set that contain the membership functions and the hybrid dynamic variables. A dynamic event-triggered fuzzy MPC algorithm is developed accordingly, whose recursive feasibility is analysed by employing the RPI set. With the designed controller, the involved fuzzy system is ensured to be asymptotically stable. Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

     

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    Highlights

    • A new dynamic event-triggered mechanism (DETM) with hybrid variables is proposed
    • This DETM enables us to save more resources and gain the anticipated performance
    • A DETM-based fuzzy MPC algorithm is devised with analysis on recursive feasibility

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