A Robust Finite-Time Fault-Tolerant Tracking Control for Quadrotor Attitude System With Stochastic Actuator Faults and Input Delays

Quadrotor unmanned aerial vehicles have become very popular for doing numerous tasks; however, due to their small size and weight, they are very sensitive to parameter uncertainties and external disturbances. In this paper, a new robust fault-tolerant approach is introduced to track the attitude trajectory of a quadrotor in finite time that suffers from stochastic actuator faults, system parameter uncertainties, and unknown external disturbances. Furthermore, the effects of time-varying input delay are considered in the control input. Based on the Lyapunov-Krasovskii functional approach, two theorems are given to derive some delay-dependent conditions regarding the design of a controller that guarantees the finite-time contractive stability of the attitude tracking error system with the prescribed H<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index. This means that the tracking error states converge to a defined bound within a fixed time interval which is smaller than the initial state bound, and the acceptable H<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> disturbance attenuation level is achieved. Finally, the proposed method is applied to a quadrotor facing the external disturbance and stochastic actuator fault. The simulation results verify the effectiveness and superiority of the proposed control scheme as compared to the asymptotic stability approach and the finite-time boundedness stability model.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3559180
Citations
11
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
13.36
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article

A Robust Finite-Time Fault-Tolerant Tracking Control for Quadrotor Attitude System With Stochastic Actuator Faults and Input Delays

Farzaneh Jani, Ebrahim Ghaderpour, Khalid A. Alattas, Ardashir Mohammadzadeh et al.
11 citations
IEEE Access
Adaptive Control of Nonlinear Systems
13.36
article

A Robust Finite-Time Fault-Tolerant Tracking Control for Quadrotor Attitude System With Stochastic Actuator Faults and Input Delays

Farzaneh Jani, Ebrahim Ghaderpour, Khalid A. Alattas, Ardashir Mohammadzadeh, V.T. Mai
article en
11 citations

Abstract

Quadrotor unmanned aerial vehicles have become very popular for doing numerous tasks; however, due to their small size and weight, they are very sensitive to parameter uncertainties and external disturbances. In this paper, a new robust fault-tolerant approach is introduced to track the attitude trajectory of a quadrotor in finite time that suffers from stochastic actuator faults, system parameter uncertainties, and unknown external disturbances. Furthermore, the effects of time-varying input delay are considered in the control input. Based on the Lyapunov-Krasovskii functional approach, two theorems are given to derive some delay-dependent conditions regarding the design of a controller that guarantees the finite-time contractive stability of the attitude tracking error system with the prescribed H<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index. This means that the tracking error states converge to a defined bound within a fixed time interval which is smaller than the initial state bound, and the acceptable H<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> disturbance attenuation level is achieved. Finally, the proposed method is applied to a quadrotor facing the external disturbance and stochastic actuator fault. The simulation results verify the effectiveness and superiority of the proposed control scheme as compared to the asymptotic stability approach and the finite-time boundedness stability model.

IEEE AccessVol. 13
Sakarya University (TR), University of Jeddah (SA), Lac Hong University (VN), Sapienza University of Rome (IT)
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Adaptive Control of Nonlinear Systems
13.36
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