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Switching mechanism-based event-triggered fuzzy adaptive control with prescribed performance for MIMO nonlinear systems

  • * Corresponding author: Yongming Li

    * Corresponding author: Yongming Li 

This work is supported by National Natural Science Foundation (NNSF) of China under Grant 62173172 and Grant 61822307

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  • This paper investigates the switching mechanism-based event-trig-gered fuzzy adaptive control issue of multi-input and multi-output (MIMO) nonlinear systems with prescribed performance (PP). Utilizing fuzzy logic systems (FLSs) to approximate unknown nonlinear functions. By using the switching threshold strategy, the system has more flexibility in strategy selection. The proposed control scheme can better solve the communication resource limitation. On account of the Lyapunov stability theory, the stability of the controlled system is proved. And all signals of the controlled system are bounded. Moreover, the tracking errors are controlled in a diminutive realm of the origin within the PP bounded. Simultaneously, the Zeno behavior is avoided. Finally, illustrate the effectiveness of the control scheme that has been proposed by demonstrating some simulation consequences.

    Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

    Citation:

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  • Figure 1.  System output $ {y_1} $ and the reference signal $ {y_{1,r}} $

    Figure 2.  System tracking error $ {y_1} - {y_{1,r}} $

    Figure 3.  Control signal

    Figure 4.  The time intervals $ {t_{kk + 1}} - {t_k} $ of triggering events

    Figure 5.  System output $ {y_2} $ and the reference signal $ {y_{2,r}} $

    Figure 6.  System tracking error $ {y_2} - {y_{2,r}} $

    Figure 7.  Control signal

    Figure 8.  The time intervals $ {t_{kk + 1}} - {t_k} $ of triggering events

    Figure 9.  Tracking performance

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