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

Ruitong Wu; Yongming Li; Jun Hu; Wei Liu; Shaocheng Tong

doi:10.3934/dcdss.2021168

Article Contents

2022, Volume 15, Issue 7: 1713-1731. Doi: 10.3934/dcdss.2021168

This issue Previous Article Finite-time sliding mode control for UVMS via T-S fuzzy approach Next Article Collision-avoidance and flocking in the Cucker–Smale-type model with a discontinuous controller

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

1.
College of Electrical Engineering, Liaoning University of Technology, Jinzhou, China
2.
College of Science, Liaoning University of Technology, Jinzhou, China
3.
Northeastern University, Shenyang, China
4.
College of Science, Liaoning University of Technology, Jinzhou, China

^* Corresponding author: Yongming Li
^* Corresponding author: Yongming Li

Received: September 2021

Revised: October 2021

Early access: December 2021

Published: July 2022

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

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Abstract

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.

Keywords:

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}} $

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

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Figure 3. Control signal

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

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

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

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Figure 7. Control signal

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

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Figure 9. Tracking performance

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