Have a personal or library account? Click to login
Towards a Health–Aware Fault Tolerant Control of Complex Systems: A Vehicle Fleet Case Cover

Towards a Health–Aware Fault Tolerant Control of Complex Systems: A Vehicle Fleet Case

Open Access
|Dec 2022

References

  1. AlShorman, O., Alkahatni, F., Masadeh, M., Irfan, M., Glowacz, A., Althobiani, F., Kozik, J. and Glowacz, W. (2021). Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study, Advances in Mechanical Engineering 13(2): 1687814021996915.10.1177/1687814021996915
  2. AlShorman, O., Irfan, M., Saad, N., Zhen, D., Haider, N., Glowacz, A. and AlShorman, A. (2020). A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor, Shock and Vibration 2020, Article ID: 8843759.10.1155/2020/8843759
  3. Anis, M.D. (2018). Towards remaining useful life prediction in rotating machine fault prognosis: An exponential degradation model, Condition Monitoring and Diagnosis (CMD), Bentley, Australia, pp. 1–6, DOI: 10.1109/CMD.2018.8535765.
  4. Arablouei, R. and Doğançay, K. (2013). Modified quasi-OBE algorithm with improved numerical properties, Signal Processing 93(4): 797–803.10.1016/j.sigpro.2012.09.024
  5. Butkovic, P. (2010). Max-Linear Systems: Theory and Algorithms, Springer, London.10.1007/978-1-84996-299-5
  6. Chen, Y., Peng, G., Zhu, Z. and Li, S. (2020). A novel deep learning method based on attention mechanism for bearing remaining useful life prediction, Applied Soft Computing 86: 105–919.10.1016/j.asoc.2019.105919
  7. Chudnovsky, B.H. (2012). Electrical Power Transmission and Distribution, CRC Press, Boca Raton.
  8. De Schutter, B. and Van Den Boom, T. (2001). Model predictive control for max-plus-linear discrete event systems, Auto-matica 37(7): 1049–1056.10.1016/S0005-1098(01)00054-1
  9. Do, N.V., Nguyen, H.D. and Selamat, A. (2018). Knowledge-based model of expert systems using Rela-model, International Journal of Software Engineering and Knowledge Engineering 28(08): 1047–1090.10.1142/S0218194018500304
  10. Duan, Z., Wu, T., Guo, S., Shao, T., Malekian, R. and Li, Z. (2018). Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: A review, International Journal of Advanced Manufacturing Technology 96(1): 803–819.10.1007/s00170-017-1474-8
  11. Gao, Z. and Liu, X. (2021). An overview on fault diagnosis, prognosis and resilient control for wind turbine systems, Processes 9(2): 300.10.3390/pr9020300
  12. Gebraeel, N., Lawley, M., Li, R. and Ryan, J. (2005). Residual-life distributions from component degradation signals: A Bayesian approach, IIE Transactions 37(6): 543–557.10.1080/07408170590929018
  13. Hamdi, H., Rodrigues, M., Rabaoui, B. and Benhadj Braiek, N. (2021). A fault estimation and fault-tolerant control based sliding mode observer for LPV descriptor systems with time delay, International Journal of Applied Mathematics and Computer Science 31(2): 247–258, DOI: 10.34768/amcs-2021-0017.
  14. Jain, T. and Yamé, J. (2020). Health-aware fault-tolerant receding horizon control of wind turbines, Control Engineering Practice 95: 104236.10.1016/j.conengprac.2019.104236
  15. Kraus, T., Mandour, G.I. and Joachim, D. (2007). Estimating the error bound in QOBE vowel classification, 50th Midwest Symposium on Circuits and Systems, Montreal, Canada, pp. 369–372.
  16. Li, N., Lei, Y., Lin, J. and Ding, S. (2015). An improved exponential model for predicting remaining useful life of rolling element bearings, IEEE Transactions on Industrial Electronics 62(12): 7762–7773.10.1109/TIE.2015.2455055
  17. Li, X., Ding, Q. and Sun, J.-Q. (2018). Remaining useful life estimation in prognostics using deep convolution neural networks, Reliability Engineering & System Safety 172: 1–11.10.1016/j.ress.2017.11.021
  18. Lipiec, B., Mrugalski, M. and Witczak, M. (2021). Health-aware fault-tolerant control of multiple cooperating autonoumous vehicles, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Luxembourg, Luxembourg, pp. 1–7.
  19. Liu, Z. and Zhang, L. (2020). A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings, Measurement 149: 107002.10.1016/j.measurement.2019.107002
  20. Majdzik, P., Akielaszek-Witczak, A., Seybold, L., Stetter, R. and Mrugalska, B. (2016). A fault-tolerant approach to the control of a battery assembly system, Control Engineering Practice 55: 139–148.10.1016/j.conengprac.2016.07.001
  21. Majdzik, P., Witczak, M., Lipiec, B. and Banaszak, Z. (2021). Integrated fault-tolerant control of assembly and automated guided vehicle-based transportation layers, International Journal of Computer Integrated Manufacturing 35(4–5): 1–18.10.1080/0951192X.2021.1872103
  22. Mrugalski, M. and Korbicz, J. (2007). Least mean square vs. outer bounding ellipsoid algorithm in confidence estimation of the GMDH neural networks, in B. Beliczyński et al. (Eds), Adaptive and Natural Computing Algorithms, Part 2, Lecture Notes in Computer Science, Vol. 4432, Springer, Berlin, p. 19.
  23. Nath, A.G., Udmale, S.S. and Singh, S.K. (2021). Role of artificial intelligence in rotor fault diagnosis: A comprehensive review, Artificial Intelligence Review 54(4): 2609–2668.10.1007/s10462-020-09910-w
  24. Nectoux, P.R.G., Medjaher, K., Ramasso, E., Morello, B., Zerhouni, N. and Varnier., C. (2012). PRONOSTIA: An experimental platform for bearings accelerated life test, IEEE International Conference on Prognostics and Health Management, Denver, USA, pp. 1–8.
  25. Pazera, M., Buciakowski, M., Witczak, M. and Mrugalski, M. (2020). A quadratic boundedness approach to a neural network-based simultaneous estimation of actuator and sensor faults, Neural Computing & Applications 32(2, SI): 379–389.10.1007/s00521-018-3706-8
  26. Salazar, J.C., Sanjuan, A., Nejjari, F. and Sarrate, R. (2020). Health-aware and fault-tolerant control of an octorotor UAV system based on actuator reliability, International Journal of Applied Mathematics and Computer Science 30(1): 47–59, DOI: 10.34768/amcs-2020-0004.
  27. Seybold, L., Witczak, M., Majdzik, P. and Stetter, R. (2015). Towards robust predictive fault-tolerant control for a battery assembly system, International Journal of Applied Mathematics and Computer Science 25(4): 849–862, DOI: 10.1515/amcs-2015-0061.
  28. Singleton, K.R., Strangas, E.G., Cui, H. and Aviyente, S. (2015). Extended Kalman filtering for remaining-useful-life estimation of bearings, IEEE Transactions on Industrial Electronics 62(3): 1781–1790.10.1109/TIE.2014.2336616
  29. Sun, B., Li, Y., Wang, Z., Ren, Y., Feng, Q., Yang, D., Lu, M. and Chen, X. (2019). Remaining useful life prediction of aviation circular electrical connectors using vibration-induced physical model and particle filtering method, Microelectronics Reliability 92: 114–122.10.1016/j.microrel.2018.11.015
  30. Sutrisno, E., Oh, H. and Vasan, A.S.S. (2012). Estimation of remaining useful life of ball bearings using data driven methodologies, IEEE Conference on Prognostics and Health Management (PHM), Denver, USA, pp. 1–7.
  31. Tanaka, K. and Sugeno, M. (1992). Stability analysis and design of fuzzy control systems, Fuzzy Sets and Systems 45(2): 135–156.10.1016/0165-0114(92)90113-I
  32. Van Den Boom, T. and De Schutter, B. (2006). Modelling and control of discrete event systems using switching max-plus-linear systems, Control Engineering Practice 14(10): 1199–1211.10.1016/j.conengprac.2006.02.006
  33. Wang, C., Lu, N., Wang, S., Cheng, Y. and Jiang, B. (2018). Dynamic long short-term memory neural-network-based indirect remaining-useful-life prognosis for satellite lithium-ion battery, Applied Sciences 8(11): 2078.10.3390/app8112078
  34. Wei, Y., Li, Y., Xu, M. and Huang, W. (2019). A review of early fault diagnosis approaches and their applications in rotating machinery, Entropy 21(4): 409, DOI: 10.3390/e21040409.751489833267123
  35. Witczak, M. (2014). Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems, Springer, Heidelberg.10.1007/978-3-319-03014-2
  36. Witczak, M., Lipiec, B., Mrugalski, M., Seybold, L. and Banaszak, Z. (2020a). Fuzzy modelling and robust fault-tolerant scheduling of cooperating forklifts, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, UK, pp. 1–10.10.1109/FUZZ48607.2020.9177782
  37. Witczak, M., Majdzik, P., Stetter, R. and Lipiec, B. (2020b). A fault-tolerant control strategy for multiple automated guided vehicles, Journal of Manufacturing Systems 55: 56–68.10.1016/j.jmsy.2020.02.009
  38. Witczak, M., Mrugalski, M., Pazera, M. and Kukurowski, N. (2020c). Fault diagnosis of an automated guided vehicle with torque and motion forces estimation: A case study, ISA Transactions 104: 370–381.10.1016/j.isatra.2020.05.01232439131
  39. Xie, X., Ma, D., Yue, D. and Xia, J. (2021). Gain-scheduling fault estimation for discrete-time Takagi–Sugeno fuzzy systems: A depth partitioning approach, IEEE Transactions on Circuits and Systems I: Regular Papers 69(4): 1693–1703.10.1109/TCSI.2021.3135911
  40. Yan, R. and Gao, R.X. (2009). Multi-scale enveloping spectrogram for vibration analysis in bearing defect diagnosis, Tribology International 42(2): 293–302.10.1016/j.triboint.2008.06.013
  41. Zadeh, L.A. (1992). Knowledge representation in fuzzy logic, in R.R.Yager and L.A. Zadeh (Eds), An Introduction to Fuzzy Logic Applications in Intelligent Systems, Springer, Boston, pp. 1–25.10.1007/978-1-4615-3640-6_1
  42. Zhang, L., Mu, Z. and Sun, C. (2018). Remaining useful life prediction for lithium-ion batteries based on exponential model and particle filter, IEEE Access 6: 17729–17740.10.1109/ACCESS.2018.2816684
  43. Zhou, Y., Huang, Y., Pang, J. and Wang, K. (2019). Remaining useful life prediction for supercapacitor based on long short-term memory neural network, Journal of Power Sources 440: 227149.10.1016/j.jpowsour.2019.227149
DOI: https://doi.org/10.34768/amcs-2022-0043 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 619 - 634
Submitted on: Jan 5, 2022
Accepted on: Jun 30, 2022
Published on: Dec 30, 2022
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Bogdan Lipiec, Marcin Mrugalski, Marcin Witczak, Ralf Stetter, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.