A novel robust fault detection method for induction motor rotor by using unknown input observer

References

• Bonnett, A. H., & Soukup, G. C. (1992). Cause and analysis of stator and rotor failures in three-phase squirrel-cage induction motors. IEEE Transactions on Industry Applications, 28, 921–937. doi: 10.1109/28.148460
   Web of Science ®Google Scholar
• Gonzalez-Prieto, H. G. I., Duran, M. J., Barrero, F., Bermudez, M., & Guzmán, H. (2017). Impact of post-fault flux adaptation on six-phase induction motor drives with parallel converters. IEEE Transactions on Power Electronics, 32, 515–528. doi: 10.1109/TPEL.2016.2533719
   Web of Science ®Google Scholar
• Guzman, H., Duran, M., Barrero, F., Zarri, L., Bogado, B., Gonzalez-Prieto, I., & Arahal, M. (2016). Comparative Study of Predictive and Resonant Controllers in fault-tolerant Five-phase induction motor drives. IEEE Transactions on Industrial Electronics, 63, 606–617. doi: 10.1109/TIE.2015.2418732
   Web of Science ®Google Scholar
• Henao, H., Capolino, G., Fernandez-Cabanas, M., Filippetti, F., Bruzzese, C., Strangas, E., … Hedayati-Kia, S. (2014). Trends in fault diagnosis for Electrical machines: A Review of Diagnostic techniques. IEEE Industrial Electronics Magazine, 8, 31–42. doi: 10.1109/MIE.2013.2287651
   Web of Science ®Google Scholar
• Imani, H., Jahed-Motlagh, M. R., Salahshoor, K., Ramezani, A., & Moarefianpur, A. (2017). A novel tube model predictive control for surge instability in compressor system including piping acoustic. Cogent Engineering, 4(1). doi: 10.1080/23311916.2017.1409373
   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, Germany: Springer Verlag.
   Google Scholar
• Jiahui, L., Hongli, D., Fei, H., Nan, H., & & Xuerong, L. (2017). Filter design, fault estimation and reliable control for networked time-varying systems: A survey. Systems Science & Control Engineering, 5(1), 331–341. doi: 10.1080/21642583.2017.1355760
   Web of Science ®Google Scholar
• Khan, A., & Ding, S. (2011). Threshold computation for fault detection in a class of discrete-time nonlinear systems. International Journal of Adaptive Control and Signal Processing, 25, 407–429. doi: 10.1002/acs.1205
   Web of Science ®Google Scholar
• Khania, F., & Haeri, M. (2015). Smooth switching in a scheduled robust model predictive controller. Journal of Process Control, 31, 55–63. doi: 10.1016/j.jprocont.2015.04.003
   Web of Science ®Google Scholar
• Mohammadpour, A., & Parsa, L. (2015). Global fault-tolerant control technique for multi-phase permanent-magnet machines. IEEE Transactions on Industry Applications, 51, 178–186. doi: 10.1109/TIA.2014.2326084
   Web of Science ®Google Scholar
• Sharifuddin, M., Ch, G., & Kingshook, B. (2010). LMI approach to robust unknown input observer design for Continuous systems with noise and uncertainties. International Journal of Control, Automation and Systems, 8, 210–219. doi: 10.1007/s12555-010-0205-9
   Web of Science ®Google Scholar
• Taleb Ziabari, M., Jahed-Motlagh, M. R., Salahshoor, K., Ramezani, A., & Moarefianpur, A. (2017). Robust adaptive control of surge instability in constant speed centrifugal compressors using tube-MPC. Cogent Engineering, 4(1). doi: 10.1080/23311916.2017.1339335
   Web of Science ®Google Scholar
• Thomson, W. T. (1998). On-line current monitoring and application of a finite element method to predict the level of static airgap eccentricity in three-phase induction motors. IEEE Transactions on Energy Conversion, 13, 347–357. doi: 10.1109/60.736320
   Web of Science ®Google Scholar
• Xianye, B., Hongli, D., Fei, H., & Gongfa, L. (2018). Event-triggered distributed filtering over sensor networks with deception attacks and partial measurements. International Journal of General Systems, 47(5), 522–534. doi: 10.1080/03081079.2018.1462353
   Web of Science ®Google Scholar
• Zandi, O., & Poshtan, J. (2017). Broken-bar rotor fault detection in squirrel-cage induction motors at presence of sensor faults using adaptive Unscented kalman filter. In 5th International Conference on control, Instrumentation, and Automation (ICCIA) (pp. 296–300). Shiraz. doi: 10.1109/ICCIAutom.2017.8258696
   Google Scholar