access icon free Integrated trade-off design of fault detection system for linear discrete time-varying systems

In this study, the problem of fault detection (FD) system design for linear discrete time-varying systems is addressed. Different from most existing methods which separately handle residual generator and evaluator, this study focuses on integrated design of residual generator and evaluator. Instead of traditional trade-off design between sensitivity to faults and robustness to disturbances, this study aims at maximising FD rate given a predefined false alarm rate. The proposed approach in this study follows two steps: first, in the norm-based framework, the parity relation-based offline FD system achieves maximal FD rate by minimising the set of undetectable faults; then the optimal offline FD system is equivalently transformed into a recursive FD algorithm for online use. Relationship between the obtained solution in this study and the existing ones is analysed. The performance improvement of the proposed approach is illustrated by comparing against existing methods through Monte Carlo simulations.

Inspec keywords: minimisation; linear systems; control system synthesis; fault diagnosis; discrete systems; sensitivity; time-varying systems; recursive estimation

Other keywords: optimal offline FD system; maximal FD rate; FD rate maximisation; FD system design; norm-based framework; performance improvement; evaluator; parity relation-based offline FD system; residual generator handling; false alarm rate; undetectable fault set minimisation; fault detection system design; linear discrete time-varying system; fault sensitivity; integrated trade-off design; recursive FD algorithm; disturbance robustness

Subjects: Time-varying control systems; Control system analysis and synthesis methods; Optimisation techniques; Discrete control systems

References

    1. 1)
      • 5. Zhang, P., Ding, S.X., Liu, P.: ‘A lifting based approach to observer based fault detection of linear periodic systems’, IEEE Trans. Autom. Control, 2012, 2, (57), pp. 457462 (doi: 10.1109/TAC.2011.2166712).
    2. 2)
      • 23. Liu, N., Zhou, K.: ‘Optimal robust fault detection for linear discrete time systems’. Proc. 46th IEEE Conf. Decision and Control, New Orleans, LA, 2007, pp. 989994.
    3. 3)
      • 10. Yao, X., Wu, L., Zheng, W.: ‘Fault detection filter design for Markovian jump singular systems with intermittent measurements’, IEEE Trans. Signal Process., 2011, 7, (59)..
    4. 4)
      • 1. Chen, J., Ratton, R.J.: ‘Robust model-based fault diagnosis for dynamic systems’ (Kluwer Academic Publishers, 1999).
    5. 5)
      • 6. Han, Y., Oh, S., Choi, B., Kwak, D., Kim, H.J., Kim, Y.: ‘Fault detection and identification of aircraft control surface using adaptive observer and input bias estimator’, IET Control Theory  Appl., 2012, 10, (6), pp. 13671387 (doi: 10.1049/iet-cta.2010.0724).
    6. 6)
      • 4. Mao, Z.H., Jiang, B., Shi, P.: ‘H∞ fault detection filter design for networked control systems modelled by discrete Markovian jump systems’, IET Control Theory  Appl., 2007, 1, (5), pp. 13361343 (doi: 10.1049/iet-cta:20060431).
    7. 7)
      • 3. Ding, S.X.: ‘Model-based fault diagnosis techniques: design schemes, algorithms, and tools’ (Springer-Verlag, 2008).
    8. 8)
      • 11. Dai, X., Gao, Z., Breikin, T., Wang, H.: ‘Zero assignment for robust H2/H∞ fault detection filter design’, IEEE Trans. Signal Process., 2009, 57, (4), pp. 13631372 (doi: 10.1109/TSP.2008.2010598).
    9. 9)
      • 8. Henry, D., Zolghadri, A.: ‘Norm-based design of robust FDI schemes for uncertain systems under feedback control: Comparison of two approaches’, Control Eng. Pract., 2006, 14, (9), pp. 10811097 (doi: 10.1016/j.conengprac.2005.06.007).
    10. 10)
      • 14. Ding, S.X., Frank, P.M., Ding, E.L., Jeinsch, T.: ‘Fault detection system design based on a new trade-off strategy’. Proc. 39th IEEE Conf. Decision and Control, Sydney, Australia, 2000, pp. 41444149.
    11. 11)
      • 13. Rambeaux, F., Hamelin, F., Sauter, D.: ‘Optimal thresholding for robust fault detection of uncertain systems’, Int. J. Robust and Nonlinear Control, 2000, 10, (14), pp. 11551173 (doi: 10.1002/1099-1239(20001215)10:14<1155::AID-RNC521>3.0.CO;2-V).
    12. 12)
      • 17. Ding, S.X., Jeinsch, T., Frank, P.M., Ding, E.L.: ‘A unified approach to the optimization of fault detection systems’, Int. J. Adapt. Control Signal Process., 2000, 14, (7), pp. 725745 (doi: 10.1002/1099-1115(200011)14:7<725::AID-ACS618>3.0.CO;2-Q).
    13. 13)
      • 19. Zhong, M., Ding, S.X., Ding, E.L.: ‘Optimal fault detection for linear discrete time-varying systems’, Automatica, 2010, 46, (8), pp. 13951400 (doi: 10.1016/j.automatica.2010.05.022).
    14. 14)
      • 12. Johansson, A., Bask, M., Norlander, T.: ‘Dynamic threshold generators for robust fault detection in linear systems with parameter uncertainty’, Automatica, 2006, 42, (7), pp. 10951106 (doi: 10.1016/j.automatica.2006.02.009).
    15. 15)
      • 9. Zhao, H., Zhong, M., Zhang, M.: ‘H∞ fault detection for linear discrete time-varying systems with delayed state’, IET Control Theory  Appl., 2010, 4, (11), pp. 23032314 (doi: 10.1049/iet-cta.2009.0215).
    16. 16)
      • 24. Zhang, F.: ‘The Schur complement and its applications’ (Springer Science, 2005).
    17. 17)
      • 15. Zhang, P., Ding, S.X.: ‘An integrated trade-off design of observer based fault detection systems’, Automatica, 2008, 44, (7), pp. 18861894 (doi: 10.1016/j.automatica.2007.11.021).
    18. 18)
      • 16. Ding, S.X., Guo, L.: ‘An approach to time domain optimization of observer-based fault detection systems’, Int. J. Control, 1998, 69, (3), pp. 419442 (doi: 10.1080/002071798222749).
    19. 19)
      • 21. Anderson, B.D.O., Moore, J.B.: ‘Detectability and stabilizability of time-varying discrete-time linear systems’, SIAM J. Control Opt., 1981, 19, (1), pp. 2032 (doi: 10.1137/0319002).
    20. 20)
      • 22. Li, X.: ‘Fault detection filter design for linear systems’. PhD thesis, Department of Electrical and Computer Engineering, Louisiana State University, 2009.
    21. 21)
      • 7. Zhong, M., Zhou, D., Ding, S.X.: ‘On designing H fault detection filter for linear discrete time-varying systems’, IEEE Trans. Autom. Control, 2010, 55, (7), pp. 16891695 (doi: 10.1109/TAC.2010.2046921).
    22. 22)
      • 18. Li, X., Zhou, K.: ‘A time domain approach to robust fault detection of linear time-varying systems’, Automatica, 2009, 45, (1), pp. 94102 (doi: 10.1016/j.automatica.2008.07.017).
    23. 23)
      • 20. Li, X., Mo, S., Zhou, K.: ‘Fault detection for linear discrete time-varying systems’. Proc. 49th IEEE Conf. Decision and Control, Atlanta, GA, USA, 2010, pp. 762767.
    24. 24)
      • 2. Basseville, M., Nikiforov, I.: ‘Detection of abrupt changes – theory and application’ (Prentice-Hall, 1993).
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