Sliding mode observer-based fault detection for helicopter system

References

• Allahverdi, F., Ramezani, A., & Forouzanfar, M. (2020). Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers. Automatika, 61(2), 219–228. https://doi.org/10.1080/00051144.2019.1706911
   Web of Science ®Google Scholar
• Avram, R., Zhang, X., & Muse, J. (2016). Quadrotor accelerometer and gyroscope sensor fault diagnosis using nonlinear adaptive estimation methods. International Journal of Prognostics and Health Management, 7(1). https://doi.org/10.36001/ijphm.2016.v7i1.2328
   Google Scholar
• Chandra, K. P. B., Alwi, H., & Edwards, C. (2015). Fault reconstruction for a quadrotor using an LPV sliding mode observer1. IFAC-PapersOnLine, 48(21), 374–379. https://doi.org/10.1016/j.ifacol.2015.09.555
   Google Scholar
• Chen, F., Zhang, K., Jiang, B., & Wen, C. (2016). Adaptive sliding mode observer-based robust fault reconstruction for a helicopter with actuator fault. Asian Journal of Control, 18(4), 1558–1565. https://doi.org/10.1002/asjc.v18.4
   Web of Science ®Google Scholar
• Edwards, C., Spurgeon, S. K., & Patton, R. J. (2000). Sliding mode observers for fault detection and isolation. Automatica, 36(4), 541–553. https://doi.org/10.1016/S0005-1098(99)00177-6
   Web of Science ®Google Scholar
• Guzmán-Rabasa, J. A., López-Estrada, F. R., González-Contreras, B. M., Valencia-Palomo, G., Chadli, M., & Perez-Patricio, M. (2019). Actuator fault detection and isolation on a quadrotor unmanned aerial vehicle modeled as a linear parameter-varying system. Measurement and Control, 52(9–10), 1228–1239. https://doi.org/10.1177/0020294018824764
   Web of Science ®Google Scholar
• Heredia, G., & Ollero, A. (2011). Detection of sensor faults in small helicopter UAVs using observer/Kalman filter identification. Mathematical Problems in Engineering, 2011, 174618. https://doi.org/10.1155/2011/174618
   Web of Science ®Google Scholar
• Heredia, G., Ollero, A., Bejar, M., & Mahtani, R. (2008). Sensor and actuator fault detection in small autonomous helicopters. Mechatronics, 18(2), 90–99. https://doi.org/10.1016/j.mechatronics.2007.09.007
   Web of Science ®Google Scholar
• Lan, J., Patton, R. J., & Zhu, X. (2017). Integrated fault-tolerant control for a 3-DOF helicopter with actuator faults and saturation. IET Control Theory & Applications, 11(14), 2232–2241. https://doi.org/10.1049/cth2.v11.14
   Web of Science ®Google Scholar
• Lianghao, H., Pu, Y., & Zhixia, Y. (2013). The application of adaptive sliding mode observer-based fault detection in helicopter system. In 2013 25th Chinese control and decision conference (CCDC) (pp. 4932–4934). IEEE.
   Google Scholar
• Marzat, J., Piet-Lahanier, H., Damongeot, F., & Walter, E. (2012). Model-based fault diagnosis for aerospace systems: A survey. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 226(10), 1329–1360. https://doi.org/10.1177/0954410011421717
   Web of Science ®Google Scholar
• Ng, K. Y., Tan, C. P., Edwards, C., & Kuang, Y. C. (2007). New results in robust actuator fault reconstruction for linear uncertain systems using sliding mode observers. International Journal of Robust and Nonlinear Control: IFAC-Affiliated Journal, 17(14), 1294–1319. https://doi.org/10.1002/(ISSN)1099-1239
   Web of Science ®Google Scholar
• Qi, X., Theilliol, D., Qi, J., Zhang, Y., & Han, J. (2013). A literature review on fault diagnosis methods for manned and unmanned helicopters. In 2013 international conference on unmanned aircraft systems (ICUAS) (pp. 1114–1118). IEEE.
   Google Scholar
• Rotondo, D., Cristofaro, A., Johansen, T. A., Nejjari, F., & Puig, V. (2016). Detection of icing and actuators faults in the longitudinal dynamics of small UAVs using an LPV proportional integral unknown input observer. In 2016 third conference on control and fault-tolerant systems (SYSTOL) (pp. 690–697). IEEE.
   Google Scholar
• Sansón, L. F., de Campos, V. A., & Potts, A. S. (2020). Robust model-based fault detection and isolation of a six degree of freedom helicopter. In Congresso brasileiro de automática-cba (Vol. 2).
   Google Scholar
• Spurgeon, S. K. (2008). Sliding mode observers: A survey. International Journal of Systems Science, 39(8), 751–764. https://doi.org/10.1080/00207720701847638
   Web of Science ®Google Scholar
• Wang, B., Huang, P., & Zhang, W. (2021). A robust fault-tolerant control for quadrotor helicopters against sensor faults and external disturbances. Complexity. https://doi.org/10.1155/2021/6672812
   Web of Science ®Google Scholar
• Wang, R., Wang, C., Sun, H., Chen, Z., & Sun, Y. (2019). Sensor fault signal reconstruction based on sliding mode observer for flight control systems. International Journal of Modelling, Identification and Control, 32(3–4), 204–211. https://doi.org/10.1504/IJMIC.2019.103665
   Web of Science ®Google Scholar
• Yan, K., Chen, M., Wu, Q., & Jiang, B. (2019). Extended state observer-based sliding mode fault-tolerant control for unmanned autonomous helicopter with wind gusts. IET Control Theory & Applications, 13(10), 1500–1513. https://doi.org/10.1049/cth2.v13.10
   Web of Science ®Google Scholar
• Yan, X. G., & Edwards, C. (2007). Nonlinear robust fault reconstruction and estimation using a sliding mode observer. Automatica, 43(9), 1605–1614. https://doi.org/10.1016/j.automatica.2007.02.008
   Web of Science ®Google Scholar
• Zhang, Y., Chamseddine, A., Rabbath, C. A., Gordon, B. W., Su, C. Y., Rakheja, S., Fulford, C., Apkarian, J., & Gosselin, P. (2013). Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed. Journal of the Franklin Institute, 350(9), 2396–2422. https://doi.org/10.1016/j.jfranklin.2013.01.009
   Web of Science ®Google Scholar
• Zhang, Z., & Xiao, B. (2020). Sensor fault reconstruction based on adaptive sliding mode observer for forklift fault-tolerant control system. Applied Sciences, 10(4), 1278. https://doi.org/10.3390/app10041278
   Google Scholar
• Zolghadri, A. (2012). Advanced model-based FDIR techniques for aerospace systems: Today challenges and opportunities. Progress in Aerospace Sciences, 53, 18–29. https://doi.org/10.1016/j.paerosci.2012.02.004
   Web of Science ®Google Scholar