Sensor Fault Diagnosis in Quadrotors Using Nonlinear Adaptive Estimators



Remus C Avram Xiaodong Zhang Jacob Campbell


Unmanned Aerial Vehicles (UAVs) have attracted significant attentions in recent years due to their potentials in various military and civilian applications. Small UAVs are often e- quipped with low-cost and lightweight micro-electro-mechanical systems (MEMS) inertial measurement units including 3-axis gyro, accelerometer and magnetometer. The measurements provided by gyros and accelerometers often suffer from bias and excessive noise as a result of temperature variations, vibration, etc. This paper presents a sensor fault diagnostic method for quadrotor UAVs. Specifically, we consider the faults in the gyro and accelerometer. A model-based sensor fault detection and isolation (FDI) estimation method is presented. The proposed FDI method adopts the idea that accelerometer and gyroscopic measurements coincide with the translational and rotational forces represented in the UAV dynamics. Thus, the faults in accelerometer and gyroscope can be represented as virtual actuator faults in the quadrotor state equations. Two diagnostic estimators are designed to provide structured FDI residuals allowing simultaneous detection and isolation of gyroscope and accelerometer sensor bias. In addition, nonlinear adaptive estimators are designed to provide an estimate of the unknown sensor bias. The parameter convergence property of the adaptive estimation scheme is an- alyzed. Simulation studies utilizing a nonlinear quadrotor UAV model are used to illustrate the effectiveness of the proposed method.

How to Cite

C Avram, R. ., Zhang, X. ., & Campbell, J. . (2014). Sensor Fault Diagnosis in Quadrotors Using Nonlinear Adaptive Estimators. Annual Conference of the PHM Society, 6(1).
Abstract 94 | PDF Downloads 58



Sensor Fault, Accelerometer and Gyro Fault, Health Diagnostic, Adaptive Obserever, nonlinear

Bangura, M., & Mahony, R. (2012). Nonlinear dynamic modeling for high performance control of a quadrotor. In Proceedings of Austrasian Conference on Robotics and Automation.

Blanke, M., Kinnaert, M., Lunze, J., & Staroswiecki, M. (2005). Diagnosis and Fault-Tolerant Control. Springer.

Bramwell, A., Done, G., & Balmford, D. (2001). Bramwell’s Helicopter Dynamics. Oxford: Butterworth- Heinemann.

Castillo, P., Lozano, R., & Dzul, A. (2005). Modelling and Control of Mini-Flying Machines. Springer-Verlag.

Dydek, Z. T., Annaswamy, A. M., & Lavretsky, E. (2013). Adaptive control of quadrotors uavs: A design trade study with flight evaluations. IEEE Transaction on Automatic Control Systems Technology, 21(4).

Freddi, A., Longhi, S., & Monteriu ́, A. (2009). A model- based fault diagnosis system for a mini-quadrotor. In 7th Workshop on Advanced Control and Diagnosis.

Guenard, N., Hamel, T., & Mahony, R. (2008). A practical visual servo control for an unmanned aerial vehicle. IEEE Transaction on Robotics, 24(2).

Heredia, G., Ollero, A., Mahtani, R., & Bejar, M. (2005). Detection of sensor faults in autonomous helicopters. In International Conference on Robotics and Automation.

Ioannou, P. A., & Sun, J. (1996). Robust Adaptive Control. Dover Publications, Inc.

Ireland, M., & Anderson, D. (2012). Development of navigation algorithms for NAP-of-the-earth UAV flight in a constrained urban environment. In 28th International Congress of the Aeronautical Sciences.

Lantos, B., & Marton, L. (2011). Nonlinear Control of Vehicles and Robots. In (chap. Nonlinear Control of Airplanes and Helicopters). Springer-London.

Leishman, R. C., Jr., J. C. M., Beard, R. W., & McLain, T. (2014). Quadrotors and accelerometers. state estimation with an improved dynamic model. IEEE Control Systems Magazine, 34(1).

Martin, P., & Salau ̈n, E. (2010). The true role of accelerometer feedback in quadrotor control. In IEEE International Conference on Robotics and Automtation.

Pounds, P., Mahony, R., & Gresham, J. (2004). Towards dynamically-favourable quad-rotor aerial robots. In Australasian Conference on Robotics and Automation, ACRA.

Sharifi, F., Mirzaei, M., Gordon, B. W., & Zhang, Y. (2010). Fault tolerant control of a quadrotor UAV using slid- ing mode control. In 2010 Conference on Control and Fault Tolerant Systems.

Shima, T., & Rasmussen, S. (2008). Uav cooperative decision and control: Challenges and practical approaches. In SIAM.

US Dept. of Defense. (2000). Unmanned systems integrated roadmap,FY2000-2025 (Tech. Rep.). Secretary of Defense, Washington, D.C.

US Dept. of Defense. (2012). Unmanned systems integrated roadmap FY2011-2036 (Tech. Rep.). Secretary of Defense, Washington, D.C.

Vachtsevanos, G., Tang, L., Drozeski, G., & Gutierrez, L. (2005). From mission planning to flight control of unmanned aerial vehicles: Strategies and implementation tools. Anual
Reviews in Control, 29, 101-115.

Zhang, X. (2011). Sensor bias fault detection and isolation in a clas of nonlinear uncertain systems using adaptive estimation. IEEE Transaction on Automatic Control, 56(5).
Technical Research Papers