Fault Tolerant Control of Quadrotor Based on Sensor Fault Diagnosis and Recovery Information

Abstract

Drones have been developed for more than two decades. They have become central to the functions of various civil aviation and military services. Commercial usage of drones continues to grow steadily. As the drones have been used widely in different areas, this raises a safety concern, i.e., all the multi-rotors have an increased risk of motor or sensor faults. This paper considers a fault-tolerant control (FTC) problem against the inertial motion unit (IMU) sensor fault. First, a neural network estimator is built for the purpose of fault diagnosis. Second, a fault detection scheme is designed by comparing the IMU reading with the estimator, where it uses a logic rule to monitor the IMU state. Third, if the IMU sensor is in faulty state, the Euler angle estimator with neural network built is used to recover the IMU information which is fed into the controller designed. Finally, simulation studies are given to illustrate the effectiveness of the proposed FTC.

Keywords

• fault diagnosis
• neural networks
• sensor fault
• unmanned aerial vehicle