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Articles

Multiobjective performance-based designs in fault estimation and isolation for discrete-time systems and its application to wind turbines

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Pages 1252-1274 | Received 07 May 2018, Accepted 17 Mar 2019, Published online: 09 Apr 2019

References

  • Ahmadizadeh, S., Zarei, J., & Karimi, H. R. (2014). Robust unknown input observer design for linear uncertain time delay systems with application to fault detection. Asian Journal of Control, 16(4), 1006–1019. doi: 10.1002/asjc.765
  • Aouaouda, S., Chadli, M., Shi, P., & Karimi, H. R. (2015). Discrete-time H−/H∞ sensor fault detection observer design for nonlinear systems with parameter uncertainty. International Journal of Robust and Nonlinear Control, 25(3), 339–361. doi: 10.1002/rnc.3089
  • Blesa, J., Jiménez, P., Rotondo, D., Nejjari, F., & Puig, V. (2015). An interval NLPV parity equations approach for fault detection and isolation of a wind farm. IEEE Transactions on Industrial Electronics, 62(6), 3794–3805.
  • Blesa, J., Rotondo, D., Puig, V., & Nejjari, F. (2014). FDI and FTC of wind turbines using the interval observer approach and virtual actuators/sensors. Control Engineering Practice, 24, 138–155. doi: 10.1016/j.conengprac.2013.11.018
  • Chang, J.-L. (2006). Applying discrete-time proportional integral observers for state and disturbance estimations. IEEE Transactions on Automatic Control, 51(5), 814–818. doi: 10.1109/TAC.2006.875019
  • Chen, W., Ding, S. X., Haghani, A., Naik, A., Khan, A. Q., & Yin, S. (2011). Observer-based FDI schemes for wind turbine benchmark. In Proceedings of the IFAC world congress, Milano, Italy (pp. 7073–7078).
  • Chen, W., Khan, A., Abid, M., & Ding, S. (2011). Integrated design of observer based fault detection for a class of uncertain nonlinear systems. International Journal of Applied Mathematics and Computer Science, 21(3), 423–430. doi: 10.2478/v10006-011-0031-0
  • Chen, J., & Patton, R. J. (2012). Robust model-based fault diagnosis for dynamic systems (Vol. 3). London: Springer Science & Business Media.
  • Chen, L., Patton, R. J., & Goupil, P. (2012). Robust fault estimation and performance evaluation based upon the ADDSAFE benchmark model. IFAC Proceedings Volumes, 45(20), 1364–1369. doi: 10.3182/20120829-3-MX-2028.00211
  • Chen, J., Patton, R. J., & Zhang, H. Y. (1996). Design of unknown input observers and robust fault detection filters. International Journal of Control, 63(1), 85–105. doi: 10.1080/00207179608921833
  • Cieslak, J., Efimov, D., & Henry, D. (2015). Transient management of a supervisory fault-tolerant control scheme based on dwell-time conditions. International Journal of Adaptive Control and Signal Processing, 29(1), 123–142. doi: 10.1002/acs.2465
  • de Oliveira, M. C., Bernussou, J., & Geromel, J. C. (1999). A new discrete-time robust stability condition. Systems & Control Letters, 37(4), 261–265. doi: 10.1016/S0167-6911(99)00035-3
  • Ding, S. X. (2008). Model-based fault diagnosis techniques: Design schemes, algorithms, and tools. London: Springer Science & Business Media.
  • Ding, S. X. (2014). Data-driven design of fault diagnosis and fault-tolerant control systems. London: Springer Science & Business Media.
  • Dolz, D., Penarrocha, I., & Sanchis, R. (2015). Performance trade-offs for networked jump observer-based fault diagnosis. IEEE Transactions on Signal Processing, 63(10), 2692–2703. doi: 10.1109/TSP.2015.2419188
  • Dong, J., Wu, Y., & Yang, G. H. (2017). A new sensor fault isolation method for T–S fuzzy systems. IEEE Transactions on Cybernetics, 47(9), 2437–2447. doi: 10.1109/TCYB.2017.2707422
  • El Ghaoui, L., Oustry, F., & AitRami, M. (1997). A cone complementarity linearization algorithm for static output-feedback and related problems. IEEE Transactions on Automatic Control, 42(8), 1171–1176. doi: 10.1109/9.618250
  • Gao, Z. (2015). Fault estimation and fault-tolerant control for discrete-time dynamic systems. IEEE Transactions on Industrial Electronics, 62(6), 3874–3884.
  • Gao, Z., Cecati, C., & Ding, S. X. (2015). A survey of fault diagnosis and fault-tolerant techniques – Part I: Fault diagnosis with model-based and signal-based approaches. IEEE Transactions on Industrial Electronics, 62(6), 3757–3767. doi: 10.1109/TIE.2015.2417501
  • Gao, Z., & Ho, D. W. (2004). Proportional multiple-integral observer design for descriptor systems with measurement output disturbances. IEE Proceedings – Control Theory and Applications, 151(3), 279–288. doi: 10.1049/ip-cta:20040437
  • Gao, Z., Liu, X., & Chen, M. Z. (2016). Unknown input observer-based robust fault estimation for systems corrupted by partially decoupled disturbances. IEEE Transactions on Industrial Electronics, 63(4), 2537–2547.
  • Guerra, T. M., Márquez, R., Kruszewski, A., & Bernal, M. (2018). H∞ LMI-based observer design for nonlinear systems via Takagi–Sugeno models with unmeasured premise variables. IEEE Transactions on Fuzzy Systems, 26(3), 1498–1509. doi: 10.1109/TFUZZ.2017.2728522
  • Hassanabadi, A. H., Shafiee, M., & Puig, V. (2016). UIO design for singular delayed LPV systems with application to actuator fault detection and isolation. International Journal of Systems Science, 47(1), 107–121. doi: 10.1080/00207721.2015.1029567
  • Henrion, D., Löfberg, J., Kočvara, M., & Stingl, M. (2005). Solving polynomial static output feedback problems with PENBMI. In Proceedings of the 44th IEEE conference on decision and control, Seville, Spain (pp. 7581–7586).
  • Huang, S. J., Zhang, D. Q., Guo, L. D., & Wu, L. B. (2018). Convergent fault estimation for linear systems with faults and disturbances. IEEE Transactions on Automatic Control, 63(3), 888–893. doi: 10.1109/TAC.2017.2735547
  • Hwang, I., Kim, S., Kim, Y., & Seah, C. E. (2010). A survey of fault detection, isolation, and reconfiguration methods. IEEE Transactions on Control Systems Technology, 18(3), 636–653. doi: 10.1109/TCST.2009.2026285
  • Kočvara, M., & Stingl, M. (2003). PENNON: A code for convex nonlinear and semidefinite programming. Optimization Methods and Software, 18(3), 317–333. doi: 10.1080/1055678031000098773
  • Lan, J., & Patton, R. J. (2016). A new strategy for integration of fault estimation within fault-tolerant control. Automatica, 69, 48–59. doi: 10.1016/j.automatica.2016.02.014
  • Lan, J., & Patton, R. J. (2017). Integrated fault estimation and fault-tolerant control for uncertain lipschitz nonlinear systems. International Journal of Robust and Nonlinear Control, 27(5), 761–780. doi: 10.1002/rnc.3597
  • Lan, J., Patton, R. J., & Zhu, X. (2018). Fault-tolerant wind turbine pitch control using adaptive sliding mode estimation. Renewable Energy, 116, 219–231. doi: 10.1016/j.renene.2016.12.005
  • Li, X., Karimi, H. R., Wang, Y., Lu, D., & Guo, S. (2018). Robust fault estimation and fault-tolerant control for Markovian jump systems with general uncertain transition rates. Journal of the Franklin Institute, 355(8), 3508–3540. doi: 10.1016/j.jfranklin.2018.01.049
  • Li, Y., Karimi, H. R., Zhong, M., Ding, S. X., & Liu, S. (2018). Fault detection for linear discrete time-varying systems with multiplicative noise: The finite-horizon case. IEEE Transactions on Circuits and Systems I: Regular Papers
  • Li, Z., Mazars, E., Zhang, Z., & Jaimoukha, I. M. (2012). State-space solution to the H−/H∞ fault-detection problem. International Journal of Robust and Nonlinear Control, 22(3), 282–299. doi: 10.1002/rnc.1690
  • Li, X. J., Yan, J. J., & Yang, G. H. (2018). Adaptive fault estimation for TS fuzzy interconnected systems based on persistent excitation condition via reference signals. IEEE Transactions on Cybernetics, 99, 1–13.
  • Li, X., & Zhu, F. (2015). Simultaneous time-varying actuator and sensor fault reconstruction based on PI observer for LPV systems. International Journal of Adaptive Control and Signal Processing, 29(9), 1086–1098. doi: 10.1002/acs.2522
  • Liu, X., Gao, Z., & Chen, M. Z. Q. (2017). Takagi–Sugeno fuzzy model based fault estimation and signal compensation with application to wind turbines. IEEE Transactions on Industrial Electronics, 64(7), 5678–5689. doi: 10.1109/TIE.2017.2677327
  • Liu, X., Gao, Z., & Zhang, A. (2018). Robust fault tolerant control for discrete-time dynamic systems with applications to aero engineering systems. IEEE Access, 6, 18832–18847. doi: 10.1109/ACCESS.2018.2817548
  • Liu, M., & Shi, P. (2013). Sensor fault estimation and tolerant control for itô stochastic systems with a descriptor sliding mode approach. Automatica, 49(5), 1242–1250. doi: 10.1016/j.automatica.2013.01.030
  • Lofberg, J. (2004). YALMIP: A toolbox for modeling and optimization in MATLAB. In Proceedings of the IEEE international symposium on computer aided control systems design, Taipei, Taiwan (pp. 284–289).
  • Odgaard, P. F., & Stoustrup, J. (2012). Results of a wind turbine FDI competition. IFAC Proceedings Volumes, 45(20), 102–107. doi: 10.3182/20120829-3-MX-2028.00015
  • Odgaard, P. F., Stoustrup, J., & Kinnaert, M. (2013). Fault-tolerant control of wind turbines: A benchmark model. IEEE Transactions on Control Systems Technology, 21(4), 1168–1182. doi: 10.1109/TCST.2013.2259235
  • Odgaard, P. F., Stoustrup, J., Nielsen, R., & Damgaard, C. (2009). Observer based detection of sensor faults in wind turbines. In Proceedings of the European wind energy conference, Marseille, France (pp. 4421–4430).
  • Pashazadeh, V., Salmasi, F. R., & Araabi, B. N. (2018). Data driven sensor and actuator fault detection and isolation in wind turbine using classifier fusion. Renewable Energy, 116, 99–106. doi: 10.1016/j.renene.2017.03.051
  • Patton, R. J., & Chen, J. (2000). On eigenstructure assignment for robust fault diagnosis. International Journal of Robust and Nonlinear Control, 10(14), 1193–1208. doi: 10.1002/1099-1239(20001215)10:14<1193::AID-RNC523>3.0.CO;2-R
  • Rodrigues, M., Hamdi, H., Theilliol, D., Mechmeche, C., & BenHadj Braiek, N. (2015). Actuator fault estimation based adaptive polytopic observer for a class of LPV descriptor systems. International Journal of Robust and Nonlinear Control, 25(5), 673–688. doi: 10.1002/rnc.3236
  • 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 Proceedings of the 3rd conference on control and fault-tolerant systems (SYSTOL), Barcelona, Spain (pp. 690–697).
  • Rotondo, D., Nejjari, F., Puig, V., & Blesa, J. (2015). Model reference FTC for LPV systems using virtual actuators and set-membership fault estimation. International Journal of Robust and Nonlinear Control, 25(5), 735–760. doi: 10.1002/rnc.3258
  • Salahshoor, K., Mosallaei, M., & Bayat, M. (2008). Centralized and decentralized process and sensor fault monitoring using data fusion based on adaptive extended Kalman filter algorithm. Measurement, 41(10), 1059–1076. doi: 10.1016/j.measurement.2008.02.009
  • Sales-Setién, E., Peñarrocha, I., Dolz, D., & Sanchis, R. (2016). Performance-based design of PI observers for fault diagnosis in LTI systems under gaussian noises. In Proceedings of the 3rd conference on control and fault-tolerant systems (SYSTOL), Barcelona, Spain (pp. 407–412).
  • Sales-Setién, E., & Peñarrocha-Alós, I. (2018). Banks of estimators and decision mechanisms for pitch actuator and sensor FE in wind turbines. IFAC-PapersOnLine, 51(24), 1141–1148. doi: 10.1016/j.ifacol.2018.09.715
  • Sanchez, H., Escobet, T., Puig, V., & Odgaard, P. F. (2015). Fault diagnosis of an advanced wind turbine benchmark using interval-based ARRs and observers. IEEE Transactions on Industrial Electronics, 62(6), 3783–3793.
  • Shi, F., & Patton, R. (2015). An active fault tolerant control approach to an offshore wind turbine model. Renewable Energy, 75, 788–798. doi: 10.1016/j.renene.2014.10.061
  • Sloth, C., Esbensen, T., & Stoustrup, J. (2011). Robust and fault-tolerant linear parameter-varying control of wind turbines. Mechatronics, 21(4), 645–659. doi: 10.1016/j.mechatronics.2011.02.001
  • Wang, J., Ge, W., Zhou, J., Wu, H., & Jin, Q. (2017). Fault isolation based on residual evaluation and contribution analysis. Journal of the Franklin Institute, 354(6), 2591–2612. doi: 10.1016/j.jfranklin.2016.09.002
  • Wang, X., Tan, C. P., & Zhou, D. (2017). A novel sliding mode observer for state and fault estimation in systems not satisfying matching and minimum phase conditions. Automatica, 79, 290–295. doi: 10.1016/j.automatica.2017.01.027
  • Witczak, M., Buciakowski, M., Puig, V., Rotondo, D., & Nejjari, F. (2016). An LMI approach to robust fault estimation for a class of nonlinear systems. International Journal of Robust and Nonlinear Control, 26(7), 1530–1548. doi: 10.1002/rnc.3365
  • Witczak, M., Rotondo, D., Puig, V., Nejjari, F., & Pazera, M. (2017). Fault estimation of wind turbines using combined adaptive and parameter estimation schemes. International Journal of Adaptive Control and Signal Processing, 32, 549–567. doi: 10.1002/acs.2792
  • Wu, A. G., & Duan, G. R. (2007). Generalized PI observer design for linear systems. IMA Journal of Mathematical Control and Information, 25(2), 239–250. doi: 10.1093/imamci/dnm021
  • Wu, A. G., Feng, G., & Duan, G. R. (2012). Proportional multiple-integral observer design for discrete-time descriptor linear systems. International Journal of Systems Science, 43(8), 1492–1503. doi: 10.1080/00207721.2010.547632
  • Yin, S., Gao, H., Qiu, J., & Kaynak, O. (2017). Descriptor reduced-order sliding mode observers design for switched systems with sensor and actuator faults. Automatica, 76, 282–292. doi: 10.1016/j.automatica.2016.10.025
  • Zhang, P., & Ding, S. X. (2008). An integrated trade-off design of observer based fault detection systems. Automatica, 44(7), 1886–1894. doi: 10.1016/j.automatica.2007.11.021
  • Zhang, K., Hao, H., Chen, Z., Ding, S. X., & Peng, K. (2015). A comparison and evaluation of key performance indicator-based multivariate statistics process monitoring approaches. Journal of Process Control, 33, 112–126. doi: 10.1016/j.jprocont.2015.06.007
  • Zhang, K., Jiang, B., & Shi, P. (2012). Observer-based fault estimation and accommodation for dynamic systems (Vol. 436). London: Springer Science & Business Media.
  • Zhao, D., Shen, D., & Wang, Y. (2017). Fault diagnosis and compensation for two-dimensional discrete time systems with sensor faults and time-varying delays. International Journal of Robust and Nonlinear Control, 27(16), 3296–3320. doi: 10.1002/rnc.3742
  • Zhong, M., Zhang, L., Ding, S. X., & Zhou, D. (2017). A probabilistic approach to robust fault detection for a class of nonlinear systems. IEEE Transactions on Industrial Electronics, 64(5), 3930–3939. doi: 10.1109/TIE.2016.2637308
  • Zhou, K., Doyle, J. C., & Glover, K. (1996). Robust and optimal control (Vol. 40). Upper Saddle River, NJ: Prentice Hall.
  • Ziyabari, S. H. S., & Shoorehdeli, M. A. (2017). Robust fault diagnosis scheme in a class of nonlinear system based on UIO and fuzzy residual. International Journal of Control, Automation and Systems, 15(3), 1145–1154. doi: 10.1007/s12555-016-0145-0

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