Abstract
This paper presents the design, analysis, and real-time experimental evaluation results of a nonlinear sensor fault diagnosis scheme for quadrotor unmanned air vehicles (UAV). The objective is to detect, isolate, and estimate sensor bias faults in accelerometer and gyroscope measurements. Based on the quadrotor dynamics and sensor models under consideration, the effects of sensor faults are represented as virtual actuator faults in the quadrotor state equation. Two nonlinear diagnostic estimators are designed to provide structured residualsfor fault detection and isolation. Additionally, after the fault is detected and isolated, a nonlinear adaptive estimation scheme is employed for estimating the unknown fault magnitude.The proposed fault diagnosis scheme is capable of handling simultaneous faults in the accelerometer and gyroscope measurements. The effectiveness of the fault diagnosis method is demonstrated using an indoor real-time quadrotor UAV test environment.
Highlights
Unmanned Aerial Vehicles (UAVs) have attracted significant attentions in the recent decade due to their potentials in various military and civilian applications, including security patrol, search and rescue in hazardous environment, surveillance and classification, attack and rendezvous (Shima & Rasmussen, 2008)
Compared with manned systems, the reductions in operations and support costs offer the advantage for life cycle cost savings (US Dept. of Defense, 2012)
The objective of this research focuses on the design, analysis, and experimental demonstration of a robust fault detection, isolation, and estimation scheme for sensor bias faults in accelerometer and gyroscope measurements described by Eq (6) and Eq (7)
Summary
Unmanned Aerial Vehicles (UAVs) have attracted significant attentions in the recent decade due to their potentials in various military and civilian applications, including security patrol, search and rescue in hazardous environment, surveillance and classification, attack and rendezvous (Shima & Rasmussen, 2008). Quadrotors are often equipped with low-cost and lightweight micro-electro-mechanical systems (MEMS) inertial measurement units (IMU) including 3-axis gyroscope, accelerometer and magnetometer. These sensors serve an essential role in most quadrotor control schemes. There have been very limited real-time experimental results on quadrotor sensor fault diagnosis INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT estimating sensor bias faults in accelerometer and gyroscope measurements of quadrotor UAVs is presented. The sensor fault diagnosis method is implemented using a real-time indoor quadrotor test environment.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call