Residual based tilt tri-rotor UAV actuator fault detection using TSK fuzzy model

Undetected actuator faults on tilt tri-rotor UAVs can lead to system failures and uncontrolled crashes. Multiple flight modes result in complex models with strong nonlinearity, making fault detection of their actuators a very challenging task. To address this issue, this article proposes a fault detection method based on residual generated by using TSK fuzzy model. Initially, the flight modes of the tilt tri-rotor UAV are modeled as the TSK fuzzy model. Following this, the residual generator is employed for rapid detection of actuator failures. To enhance detection accuracy, the kernel principal component analysis (KPCA) algorithm is used for a secondary confirmation. The proposed algorithm was validated using both a simulation platform and real flight data. The results demonstrate that the fault detection algorithm achieves high accuracy and real-time performance, with a computing time of approximately 41 ms in real controller hardware, thus meeting the requirements of practical applications.