Actuator and sensor fault detection and isolation of an actuated seat via nonlinear multi-observers

REFERENCES

• Bouibed, K., Aitouche, A., & Bayart, M.(2009, August 9–12). Nonlinear parity space applied to an autonomous vehicle. IEEE international conference on mechatronics and automation, Changchun, China(pp. 198–203).
   Google Scholar
• Bouibed, K., Aitouche, A., & Bayart, M.(2010, June 23–25). Sensor and actuator fault detection and isolation using two model based approaches: Application to an autonomous electric vehicle. IEEE Mediterranean conference on control and automation, Marrakech, Morocco(pp. 1290–1295).
   Google Scholar
• Bouibed, K., Aitouche, A., Rabhi, A., & Bayart, M.(2008, June 30–July 2). Estimation of contact forces of a four-wheel steering electric vehicle by differential sliding mode observer. 1st IEEE Mediterranean conference on intelligent systems and automation, Annaba, Algeria (Vol. 1019, pp. 541–546).
   Google Scholar
• Bouibed, K., Seddiki, L., Guelton, K., & Akdag, H.(2013, October). Actuator fault detection by nonlinear sliding mode observers: Application to an actuated seat. 2nd international conference on control and fault tolerant control, Nice, France(pp. 739–743).
   Google Scholar
• Davila, J., Fridman, L., & Levant, A.(2005, November). Second-order sliding-mode observer for mechanical systems. IEEE Transactions on Automatic Control, 50(11), pp. 1785–1789. doi: 10.1109/TAC.2005.858636
   Web of Science ®Google Scholar
• Davila, J., Fridman, L., & Poznyak, A.(2006, October). Observation and identification of mechanical systems via second order sliding modes. International Journal of Control, 79(10), 1251–1262. doi: 10.1080/00207170600801635
   Web of Science ®Google Scholar
• Ding, S., Zhang, P., Naik, A., Ding, E., & Huang, B.(2009). Subspace method aided data-driven design of fault detection and isolation systems, Journal of Process Control, 19(9), 1496–1510. doi: 10.1016/j.jprocont.2009.07.005
   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. doi: 10.1016/S0005-1098(99)00177-6
   Web of Science ®Google Scholar
• Gertler, J.(1998). Fault detection and diagnosis in engineering systems. Basel, NY: CRC.
   Google Scholar
• Godwin, J. L., Matthews, P., & Watson, C.(2013). Classification and detection of electrical control system faults through SCADA data analysis. Chemical Engineering Transactions, 33, 985–990.
   Google Scholar
• Gorinevsky, D., & Nicholas, M.(2013, October). Covariance estimation in two-level regression. 2nd international conference on control and fault tolerant control, Nice, France(pp. 288–293).
   Google Scholar
• Hammouri, H., Kinnaert, M., & El Yaagoubi, E. H.(1999). Observer-based approach to fault detection and isolation for nonlinear systems. IEEE Transactions on Automatic Control, 44(10), 1879–1884. doi: 10.1109/9.793728
   Web of Science ®Google Scholar
• Hashemi, A., & Pisu, P.(2011). Adaptive threshold-Based fault detection and isolation for automotive electrical systems. 9th world congress on intelligent control and automation(pp. 1013–1018).
   Google Scholar
• Isermann, R.(1984). Process fault detection based on modeling and estimation methods – a survey. Automatica, 20(4), 387–404. doi: 10.1016/0005-1098(84)90098-0
   Web of Science ®Google Scholar
• Isermann, R.(2011). Fault-diagnosis applications: Model-based condition monitoring: Actuators, drives, machinery, plants, sensors, and fault-tolerant systems. Berlin: Springer-Verlag.
   Google Scholar
• Khalil, W., & Dombre, E.(2004). Modeling, identification and control of robots. London: Kogan Page Ltd.
   Google Scholar
• Levant, A.(1993). Sliding order and sliding accuracy in sliding mode control. International Journal of Control, 58(6), 1247–1263. doi: 10.1080/00207179308923053
   Web of Science ®Google Scholar
• Li, Z., Yan, X., Yuan, C., Zhao, J., & Peng, Z.(2011). Fault detection and diagnosis of a gearbox in marine propulsion systems using bispectrum analysis and artificial neural networks. Journal of Marine Science and Application, 10(1), 17–24. doi: 10.1007/s11804-011-1036-7
   Google Scholar
• M'sirdi, N., Rabhi, A., Fridman, L., Davila, J., & Delanne, Y.(2006, June). Second order sliding mode observer for estimation of velocities, wheel sleep, radius and stiffness. American control conference, Minneapolis, MN(pp. 3316–3321).
   Google Scholar
• M'sirdi, N., Rabhi, A., Ouladsine, M., & Fridman, L.(2006, June). First and high-order sliding mode observers to estimate the contact forces. International workshop on variable structure systems(pp. 274–279).
   Google Scholar
• Nehaoua, L., Ichalal, D., Arioui, H., Mammar, S., & Fridman, L.(2013). Lean and steering motorcycle dynamics reconstruction: An unknown input hosmo approach. American control conference, Washington, DC(pp. 7–15).
   Google Scholar
• Patton, R., Frank, P., & Clarke, R.(1989). Fault diagnosis in dynamic systems: Theory and application. Upper Saddle River, NJ: Prentice-Hall, Inc.
   Google Scholar
• RÃos, H., Edwards, C., Davila, J., & Fridman, L. M.(2012). Fault detection and isolation for nonlinear systems via HOSM multiple observer. Proceedings of the 8th IFAC symposium on fault detection, supervision and safety of technical processes, Mexico City, Mexico, (Vol. 8, pp. 534–539).
   Google Scholar
• Sangha, S., Yu, D., & Gomm, J.(2013). Sensor fault detection, isolation, accommodation and unknown fault detection in automotive engine using AI. International Journal of Engineering, Science and Technology, 4(3), 53–65.
   Google Scholar
• Seddiki, L., Guelton, K., & Zaytoon, J.(2010). Concept and Takagi-Sugeno descriptor tracking controller design of a closed muscular chain lower-limb rehabilitation device. IET Control Theory Applications, 4(8), 1407–1420. doi: 10.1049/iet-cta.2009.0269
   Web of Science ®Google Scholar
• Slotine, J. J. E., Hedrick, J. K., & Misawa, E. A.(1986). Nonlinear state estimation using sliding observers. IEEE conference on decision and control, Athen, Greece(pp. 332–339).
   Google Scholar
• Tan, C. P., & Edwards, C.(2002). Sliding mode observers for detection and reconstruction of sensor faults. Automatica, 38(10), 1815–1821. doi: 10.1016/S0005-1098(02)00098-5
   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. doi: 10.1016/j.automatica.2007.02.008
   Web of Science ®Google Scholar
• Yang, M. H., Guo, S. C., Xing, Z. R., Li, Y., & Qiu, J. Q.(2012). Actuator fault detection and isolation for robot manipulators with the adaptive observer. Advanced Materials Research, 482, 529–532.
   Google Scholar
• Zhang, X.(2011). Sensor bias fault detection and isolation in a class of nonlinear uncertain systems using adaptive estimation. IEEE Transactions on Automatic Control, 56(5), 1220–1226. doi: 10.1109/TAC.2011.2112471
   Web of Science ®Google Scholar