10.57647/j.spre.2025.0901.03

Actuator Fault Event-Triggered Compensation for Multiagent Fractional-Order Nonlinear Systems

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  • Fatemeh Gholami1,
  • Mahnaz Hashemi*1,
  • Ghazanfar Shahgholian2,
  1. Department of Electrical Engineering  AND  Digital Processing and Machine Vision Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran
  2. Department of Electrical Engineering  AND  Smart Microgrid Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran

Received: 2025-01-19

Revised: 2025-02-07

Accepted: 2025-02-14

Published 2025-03-01

Copyright (c) 2025 Fatemeh Gholami, Mahnaz Hashemi, Ghazanfar Shahgholian (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

How to Cite

Gholami, F., Hashemi, M., & Shahgholian, G. (2025). Actuator Fault Event-Triggered Compensation for Multiagent Fractional-Order Nonlinear Systems. Signal Processing and Renewable Energy (SPRE), 9(1 (March 2025). https://doi.org/10.57647/j.spre.2025.0901.03
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Abstract

This paper proposes a novel distributed adaptive dynamic event-triggered control (DADETC) scheme for uncertainties multi-agent fractional-order nonlinear systems affected by actuator faults. The proposed controller can compensate for a wide range of actuator failures without the necessity for explicit fault detection. To address the problem of the unnecessary waste of communication resources, a distributed dynamic event-triggered control (DETC) is designed. In the design process, it is assumed that only the information of the first state of the followers is available. A state observer is used to measure non-measurable states. Neural networks are used to approximate uncertainties. Then, an adaptive fault strategy is applied for compensate the loss of effectiveness and stuck actuator faults. A detailed analytical proof is presented in the following to show that the proposed strategy successfully avoids the Zeno phenomenon. Finally, the Lyapunov fractional-order stability method is employed to guarantee the boundedness of all closed-loop signals and the convergence of the tracking error to a small neighborhood of the origin.

Keywords

  • Actuator fault,
  • Adaptive control,
  • Dynamic event-triggered control,
  • Fractional-order systems,
  • Multi-agent systems,
  • Neural networks,
  • Strict-feedback systems
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