Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Fault Diagnosis of a Nonlinear Dynamic System Based on Sliding Mode

  • Yu, Wenxin (School of Information and Electrical Engineering, Hunan University of Science and Technology) ;
  • Wang, Junnian (School of Physics and Electronics, Hunan University of Science and Technology) ;
  • Jiang, Dan (School of Information and Electrical Engineering Hunan University of Science and Technology)
  • Received : 2018.03.27
  • Accepted : 2018.07.01
  • Published : 2018.11.01
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Abstract

Actuator failures and the failures of controlled objects are often considered together. To overcome this limitation, a class of sliding mode observers for the fault diagnosis of nonlinear systems is designed in this paper. Due to the influence of the sliding mode function, the control strategy and the residual change of the observer exhibit certain trends governed by specific relations. Therefore, according to the changes in the control strategy and the observer residuals, the sensor and actuator faults in nonlinear systems can be determined. Finally, the effectiveness of the proposed method is verified based on simulations of a DC motor system.

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References

  1. Emami, Kianoush, et al. "A functional observer based fault detection technique for dynamical systems," Journal of the Franklin Institute, vol. 352, no. 5, pp. 2113-2128, 2015. https://doi.org/10.1016/j.jfranklin.2015.02.006
  2. Xu, B., and F. Sun. "Composite Intelligent Learning Control of Strict-Feedback Systems with Disturbance," IEEE Transactions on Cybernetics, 48, no. 2, pp. 730-741, 2018. https://doi.org/10.1109/TCYB.2017.2655053
  3. Jeon, Yeong Beom, et al. "A Robust Output Feedback Controller Design using High gain Observer for Gimbal Systems with Dynamic Variation," Journal of Institute of Control Robotics & Systems, vol. 24, 2018.
  4. Gao Z, Breikin T, Wang H. "High-Gain Estimator and Fault-Tolerant Design With Application to a Gas Turbine Dynamic System," IEEE Transactions on Control Systems Technology, vol. 15, no. 4, pp. 740-753, 2007. https://doi.org/10.1109/TCST.2006.890282
  5. Narasimhan S. "New nonlinear residual feedback observer for fault diagnosis in nonlinear systems," Automatica, vol. 44, no. 9, pp. 2222-2229, 2008. https://doi.org/10.1016/j.automatica.2007.12.020
  6. R. Sharma. Estimation of states, "faults and unknown disturbances in non-linear systems," International Journal of Control, vol. 81, no. 8, pp. 1195-1201, 2008. https://doi.org/10.1080/00207170601087937
  7. Hwang I, Kim S, Kim Y, et al. "A Survey of Fault Detection, Isolation, and Reconfiguration Methods," IEEE Transactions on Control Systems Technology, vol. 18, no. 3, pp. 636-653, 2010. https://doi.org/10.1109/TCST.2009.2026285
  8. Veluvolu K C, Soh Y C. "Fault reconstruction and state estimation with sliding mode observers for Lipschitz non-linear systems," Iet Control Theory & Applications, vol. 5, no. 11, pp. 1255-1263, 2011. https://doi.org/10.1049/iet-cta.2010.0171
  9. Sharma R, Aldeen M. "Fault and disturbance reconstruction in non-linear systems using a network of interconnected sliding mode observers," Iet Control Theory & Applications, vol. 5, no. 6, pp. 751-763, 2011. https://doi.org/10.1049/iet-cta.2009.0592
  10. Zina, Habib Ben, et al. "Robust Sensor Fault-Tolerant Control of Induction Motor Drive," International Journal of Fuzzy Systems, pp. 1-12, 2016.
  11. Xu, Bin, et al. "Fault-tolerant control using commandfiltered adaptive back-stepping technique: Application to hypersonic longitudinal flight dynamics," International Journal of Adaptive Control & Signal Processing, vol. 30, no. 4, pp. 553-577, 2016. https://doi.org/10.1002/acs.2596
  12. Vieira, Rodrigo Padilha, T. S. Gabbi, and H. A. Grundling. "Combined Discrete-time Sliding Mode and Disturbance Observer for Current Control of Induction Motors," Journal of Control Automation & Electrical Systems, vol. 28, no. 3,, pp. 380-388, 2017. https://doi.org/10.1007/s40313-017-0307-1
  13. Tan, Pin C. "Sliding mode observers for fault detection and isolation," University of Leicester (United Kingdom), 2002.
  14. Capisani L M, Ferrara A, Pisu P. "Sliding mode observers for vision-based fault detection, isolation and identification in robot manipulators," American Control Conference. IEEE, pp. 4540-4545, 2010.
  15. Brambilla D, Capisani L M, Ferrara A, et al. "Second order sliding mode observers for Fault Detection of robot manipulators," Decision and Control, 2008. Cdc 2008. IEEE Conference on. IEEE, pp. 2949-2954, 2008.
  16. Van M, Kang H J. "Fault Tolerant Control for Robot Manipulators Using Neural Network and Second-Order Sliding Mode Observer," International Conference on Intelligent Computing. Springer Berlin Heidelberg, pp. 526-535, 2013.
  17. Xiao, Bing, S. Yin, and H. Gao. "Reconfigurable Tolerant Control of Uncertain Mechanical Systems With Actuator Faults: A Sliding Mode Observer-Based Approach," IEEE Transactions on Control Systems Technology, pp. 99(2017):1-10.
  18. Yan X G, Edwards C. "Nonlinear robust fault reconstruction and estimation using a sliding mode observer," Automatica, vol. 43, no. 9, pp. 1605-1614, 2007. https://doi.org/10.1016/j.automatica.2007.02.008
  19. Chen W, Saif M. "Actuator fault diagnosis for uncertain linear systems using a high-order slidingmode robust differentiator (HOSMRD)," International Journal of Robust & Nonlinear Control, vol. 18, no. 4-5, pp. 413-426, 2010. https://doi.org/10.1002/rnc.1201
  20. Alwi H, Edwards C. "An adaptive sliding mode differentiator for actuator oscillatory failure case reconstruction," Automatica, vol. 49, no. 2, pp. 642-651, 2013. https://doi.org/10.1016/j.automatica.2012.11.042
  21. Tan C P, Edwards C. "Sliding mode observers for detection and reconstruction of sensor faults," Automatica, vol. 38, no. 10, pp. 1815-1821, 2002. https://doi.org/10.1016/S0005-1098(02)00098-5
  22. Yu J, Liu Z. "Fault reconstruction based on sliding mode observer for linear descriptor systems," Asian Control Conference, 2009. Ascc 2009, IEEE, pp. 1132-1137, 2009.
  23. Yang Junqi,Chen Yantao, Zhu Fanglai, "Sensor fauh reconstruction for a class of uncertain systems based on sliding mode observers," Journal of Henan Polytechnic University, vol. 31, no. 4, pp. 447-452, 2012. https://doi.org/10.3969/j.issn.1673-9787.2012.04.020
  24. Sellami, T., et al. "Sliding Mode Observers-based Fault Detection and Isolation for Wind Turbinedriven Induction Generator," International Journal of Power Electronics & Drive Systems, vol. 8, no. 3, pp. 1345-1358, 2017. https://doi.org/10.11591/ijpeds.v8.i3.pp1345-1358
  25. Krishnan R. "Electric motor drives: Modeling, analysis, and control," Upper Saddle River: Prentice Hall, pp. 18-23, 2001.
  26. Hu Zheng gao, Zhao Guo rong, LiFei, Zhou Da wang." Fault diagnosis for nonlinear dynamical system based on adaptive unknown input observer," Control and Decision, vol. 31, no. 5, pp. 901-906, 2016.