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

• Main Authors: Thanaraj, T., Low, Kin Huat, Ng, Bing Feng
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: 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
• Institution: Nanyang Technological University

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...