Design of Observer-Based Fault Detection Structure for Unknown Systems using Input–Output Measurements: Practical Application to BLDC Drive

Alkaya, A. and Eker, I. (2014). Luenberger Observer-Based Sensor Fault Detection: Online Application to DC Motor. Turkish Journal of Electrical Engineering & Computer Sciences, 22(2), pp. 363–370.10.3906/elk-1203-84Search in Google Scholar

Casdagli, M. (1992). A dynamical systems approach to modeling input-output systems. In: Santa Fe Institute Studies in the Sciences of Complexity-Proceedings, Vol. 12, pp. 265–265. Addison-Wesley Publishing Co.Search in Google Scholar

Chen, W., and Saif, M. (2007). Observer-Based Strategies for Actuator Fault Detection, Isolation, and Estimation for Certain Class of Uncertain Nonlinear Systems. IET Control Theory & Applications, 1(6), pp. 1672–1680.10.1049/iet-cta:20060408Search in Google Scholar

Doan, P. T., Bui, T. L., Kim, H. K., and Kim, S. B. (2013, June). Sliding-mode observer design for sensorless vector control of AC induction motor. In: 2013 9th Asian Control Conference (ASCC), Istanbul, Turkey, 23–26 June 2013, IEEE, pp. 1–5.10.1109/ASCC.2013.6606199Search in Google Scholar

Eissa, M. A., Ahmed, M. S., Darwish, R. R., and Bassiuny, A. M. (2015a, December). Model-based sensor fault detection to brushless dc motor using Luenberger observer. In: 2015 7th International Conference on Modelling, Identification and Control (ICMIC), Sousse, Tunisia, 18–20 December 2015, IEEE, pp. 1–6.10.1109/ICMIC.2015.7409391Search in Google Scholar

Eissa, M. A., Ahmed, M. S., Darwish, R. R., and Bassiuny, A. M. (2015b, December). Improved fuzzy luenberger observer-based fault detection for BLDC motor. In: 2015 Tenth International Conference on Computer Engineering & Systems (ICCES), Cairo, Egypt, 23–24 December 2015, IEEE, pp. 167–174.10.1109/ICCES.2015.7393039Search in Google Scholar

Ellis, G. (2002). Observers in Control Systems: A Practical Guide. Elsevier.Search in Google Scholar

Frank, P. M., and Ding, X. (1997). Survey of Robust Residual Generation and Evaluation Methods in Observer-Based Fault Detection Systems. Journal of Process Control, 7(6), pp. 403–424.10.1016/S0959-1524(97)00016-4Search in Google Scholar

Gadsden, S. A., Song, Y., and Habibi, S. R. (2013). Novel Model-Based Estimators for the Purposes of Fault Detection and Diagnosis. IEEE/ASME Transactions on Mechatronics, 18(4), pp. 1237–1249.10.1109/TMECH.2013.2253616Search in Google Scholar

Hakiki, K., Mazari, B., Liazid, A., and Djaber, S. (2006). Fault Reconstruction Using Sliding Mode Observers. American Journal of Applied Sciences, 3(1), pp. 1669–1674.10.3844/ajassp.2006.1669.1674Search in Google Scholar

Heredia, G., and Ollero, A. (2009, April). Sensor fault detection in small autonomous helicopters using observer/Kalman filter identification. In: 2009 IEEE International Conference on Mechatronics, Malaga, Spain, 14–17 April 2009, IEEE, pp. 1–6.10.1109/ICMECH.2009.4957236Search in Google Scholar

Ibaraki, S., Suryanarayanan, S., and Tomizuka, M. (2005). Design of Luenberger state observers using Fixed-Structure H/sub/spl infin//Optimization and its Application to Fault Detection in Lane-Keeping Control of Automated Vehicles. IEEE/ASME Transactions on Mechatronics, 10(1), pp. 34–42.10.1109/TMECH.2004.842243Search in Google Scholar

Isermann, R. (2006). Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance. Berlin: Springer Science & Business Media.10.1007/3-540-30368-5Search in Google Scholar

Khalid, H. M., Khoukhi, A., and Al-Sunni, F. M. (2011, March). Fault detection and classification using Kalman filter and genetic neuro-fuzzy systems. In: Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, El Paso, TX, USA, 18–20 March 2011, IEEE, pp. 18–20.10.1109/NAFIPS.2011.5751925Search in Google Scholar

Ko, J. S. (1998). Asymptotically Stable Adaptive Load Torque Observer for Precision Position Control of BLDC Motor. IEE Proceedings-Electric Power Applications, 145(4), pp. 383–386.10.1049/ip-epa:19982010Search in Google Scholar

Li, X. J., and Yang, G. H. (2012). Dynamic Observer-Based Robust Control and Fault Detection for Linear Systems. IET Control Theory & Applications, 6(17), pp. 2657–2666.10.1049/iet-cta.2011.0057Search in Google Scholar

Liu, L., and Collins, E. (2006). Robust Fault Detection and Diagnosis for Permanent Magnet Synchronous Motors. The Florida State University.Search in Google Scholar

Luenberger, D. (1971). An introduction to Observers. IEEE Transactions on Automatic Control, 16(6), pp. 596–602.10.1109/TAC.1971.1099826Search in Google Scholar

Nandam, P. K., and Sen, P. C. (1988, July). Sliding mode speed control of a self controlled synchronous motor (SCSM) using an adaptive state observer. In: Third International Conference on Power Electronics and Variable-Speed Drives, London, UK, 13–15 July 1988, IET, pp. 315–318.Search in Google Scholar

Padmakumar, S., Agarwal, V., and Roy, K. (2009). A comparative study into observer based fault detection and diagnosis in DC motors: Part-I. World Academy of Science, Engineering and Technology, 51.Search in Google Scholar

Poor, H. V. (2013). An Introduction to Signal Detection and Estimation. New York: Springer Science & Business Media.Search in Google Scholar

Ruderman, M., and Iwasaki, M. (2014, July). Sensorless control of motor velocity in two-mass actuator systems with load sensing using extended state observer. In: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Besançon, France, 8–11 July 2014, IEEE, pp. 360–365.10.1109/AIM.2014.6878105Search in Google Scholar

Simani, S., Fantuzzi, C., and Patton, R. J. (2013). Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques. New York: Springer Science & Business Media.Search in Google Scholar

Sobhani, M. H., and Poshtan, J. (2012). Fault Detection and Isolation Using Unknown Input Observers with Structured Residual Generation. International Journal of Instrumentation and Control Systems, 2(2), pp. 1–12.10.5121/ijics.2012.2201Search in Google Scholar

Szabat, K., and Serkies, P. J. (2009). Design and analysis of the Luenberger observers for three-inertia system. Prace Naukowe Instytutu Maszyn, Napędów i Pomiarów Elektrycznych Politechniki Wrocławskiej, Studia i Materiały, 29, pp. 329–340.Search in Google Scholar

Szabat, K., Tran-Van, T., and Kamiński, M. (2015). A modified fuzzy Luenberger observer for a two-mass drive system. IEEE Transactions on Industrial Informatics, 11(2), pp. 531–539.10.1109/TII.2014.2327912Search in Google Scholar

Tan, C. P., and Edwards, C. (2002). Sliding Mode Observers for Detection and Reconstruction of Sensor Faults. Automatica, 38(10), pp. 1815–1821.10.1016/S0005-1098(02)00098-5Search in Google Scholar

Tarantino, R., Szigeti, F., and Colina-Morles, E. (2000). Generalized Luenberger Observer-Based Fault-Detection Filter Design: An Industrial Application. Control Engineering Practice, 8(6), pp. 665–671.10.1016/S0967-0661(99)00181-1Search in Google Scholar

Vinodh Kumar, E., and Jerome, J. (2013). Sensor Fault Detection in Dc Servo System Using Unknown Input Observer with Structured Residual Generation. Journal of Electrical Engineering, 13, pp. 225–229.Search in Google Scholar

Vinodh Kumar, E., Jovitha, J., and Ayyappan, S. (2013). Comparison of Four State Observer Design Algorithms for MIMO System. Archives of Control Sciences, 23(2), pp. 243–256.Search in Google Scholar

Weiss, L., Sanderson, A., and Neuman, C. (1987). Dynamic Sensor-Based Control of Robots with Visual Feedback. IEEE Journal on Robotics and Automation, 3(5), pp. 404–417.10.1109/JRA.1987.1087115Search in Google Scholar

Yan, X. G., and Edwards, C. (2008). Robust Sliding Mode Observer-Based Actuator Fault Detection and Isolation for a Class of Nonlinear Systems. International Journal of Systems Science, 39(4), pp. 349–359.10.1080/00207720701778395Search in Google Scholar

Yang, S. K., and Liu, T. S. (1999). State Estimation for Predictive Maintenance Using Kalman Filter. Reliability Engineering & System Safety, 66(1), pp. 29–39.10.1016/S0951-8320(99)00015-0Search in Google Scholar

Yi, J., Huang, Z., Liu, W., Yang, Y., Zhang, X., and Liu, J. (2014, May). Actuator Fault Detection Based on Robust Adaptive Observer for CCBII Braking System. In: The 26th Chinese Control and Decision Conference (2014 CCDC), Changsha, China, 31 May–2 June 2014, IEEE, pp. 2841–2846.10.1109/CCDC.2014.6852657Search in Google Scholar