Actuator fault detection and isolation on multi-rotor UAV using extreme learning neuro-fuzzy systems

Actuator fault detection and isolation on multi-rotor UAV using extreme learning neuro-fuzzy systems

Undetected partial actuator faults on multi-rotor UAVs can lead to system failures and uncontrolled crashes, necessitating the development of accurate and efficient fault detection and isolation (FDI) strategy. This paper proposes a hybrid FDI model for a quadrotor UAV that integrates an extreme lea...

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Bibliographic Details
Main Authors: Thanaraj, T., Low, Kin Huat, Ng, Bing Feng
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering::Mathematics of computing::Numerical analysis
Engineering::Aeronautical engineering::Aircraft motors and engines
Actuator Fault Detection and Isolation
Multi-Rotor Unmanned Aerial Vehicle
Extreme-Learning Machines
Neuro-Fuzzy Systems
Online Access:https://hdl.handle.net/10356/167384

Internet

https://hdl.handle.net/10356/167384

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