Gain-Adaptive Fault-Tolerant Control for High-Speed UAVs with Cascade Event-Triggered Mechanism

This paper presents a robust adaptive fault-tolerant control (FTC) strategy for the path-following maneuvering of a high-speed unmanned aerial vehicle (UAV) formation system. The designation integrates an actuator gain-adaptive mechanism which is capable of compensating partial loss of effectiveness and bias faults, with a cascaded event-triggered mechanism (ETM) that regulates both control-command updates and adaptation loops. To handle strong coupling and modeling uncertainties in the UAV dynamics, unknown nonlinear terms are approximated using a fuzzy logic system (FLS), and dynamic surface control (DSC) is employed to avoid differential explosion. A boundary-regulated intermediate control term further enhances robustness against time-varying gains. The cascaded ETM reduces communication and computation by enforcing update thresholds on control inputs and parameter-update signals. Lyapunov analysis establishes semi-global uniform ultimate boundedness of all closed-loop signals. Comparative simulations indicate improved tracking accuracy and reduced channel load relative to representative baselines.

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Publication Details

Journal
Drones
Published
2026-05-02
DOI
https://doi.org/10.3390/drones10050341
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Gain-Adaptive Fault-Tolerant Control for High-Speed UAVs with Cascade Event-Triggered Mechanism

Haoyu Zhao, Heye Xiao, Jiqiang Li, Guoqing Zhang
Drones
Adaptive Control of Nonlinear Systems
article

Gain-Adaptive Fault-Tolerant Control for High-Speed UAVs with Cascade Event-Triggered Mechanism

Haoyu Zhao, Heye Xiao, Jiqiang Li, Guoqing Zhang
article en

Abstract

This paper presents a robust adaptive fault-tolerant control (FTC) strategy for the path-following maneuvering of a high-speed unmanned aerial vehicle (UAV) formation system. The designation integrates an actuator gain-adaptive mechanism which is capable of compensating partial loss of effectiveness and bias faults, with a cascaded event-triggered mechanism (ETM) that regulates both control-command updates and adaptation loops. To handle strong coupling and modeling uncertainties in the UAV dynamics, unknown nonlinear terms are approximated using a fuzzy logic system (FLS), and dynamic surface control (DSC) is employed to avoid differential explosion. A boundary-regulated intermediate control term further enhances robustness against time-varying gains. The cascaded ETM reduces communication and computation by enforcing update thresholds on control inputs and parameter-update signals. Lyapunov analysis establishes semi-global uniform ultimate boundedness of all closed-loop signals. Comparative simulations indicate improved tracking accuracy and reduced channel load relative to representative baselines.

DronesVol. 10(5)
Northwestern Polytechnical University (CN), Dalian Maritime University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Liaoning Province
Openalex Percentile: Top 8%
Adaptive Control of Nonlinear Systems
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