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Fast-rate residual generator based on multiple slow-rate sensors

Fast-rate residual generator based on multiple slow-rate sensors

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This study puts forward the problem of fast-rate fault detection based on multiple slow-rate sensors. A fast-rate residual generator with casuality constraint is established from the multi-sensor model. Parameters of the residual generator are determined via disturbance-decoupling based on left eigenvector assignment. It is found that the condition of disturbance-decoupling is related to the multi-rate sensor sampling nature. A numerical example is given to illustrate the effectiveness of the proposed residual generator.

References

    1. 1)
    2. 2)
      • 2. Patton, R.J., Chen, J.: ‘Proc. of IFAC on Fault Detection, Supervision and Safety for Technical Processes’ (Publishing House of Pergamon, London, 1998).
    3. 3)
      • 3. Chen, J., Patton, R.: ‘Robust model-based fault diagnosis for dynamic systems’ (Kluwer Academic Publishers, Boston, 1999).
    4. 4)
    5. 5)
      • 5. Frank, P.M., Ding, S.X.: ‘Current developments in the theory of FDI’. Proc. IFAC Safeprocess, Budapest, Hungary, 2000, vol. 4, pp. 1627.
    6. 6)
      • 6. Kinnaert, M: ‘Fault diagnosis based on analytical models for linear and nonlinear systems-a tutorial’. Proc. IFAC Safeprocess, Washington, USA, 2003, vol. 12, pp. 3750.
    7. 7)
    8. 8)
      • 8. Cocquempot, V., Mezyani, T.EI., Staroswiecki, M.: ‘Fault detection and isolation for hybrid systems using structured parity residuals’. Proc. fifth Asian Control Conf., Melbourne, Australia, 2004, vol. 5, pp. 12041212.
    9. 9)
      • 9. Chen, T., Francis, B.: ‘Optimal sampled-data control systems’ (Springer-Verlag, New York, 1995).
    10. 10)
      • 10. Fadali, M.S., Liu, W.: ‘Fault detection for systems with multirate sampling’. Proc. 1998 American Control Conf., Philadelphia, PA, 1998, vol. 11, pp. 33023306.
    11. 11)
      • 11. Fadali, M.S., Liu, W.: ‘Observer-based robust fault detection for a class of multirate sampled-date linear system’. Proc. American Control Conf., Philadelphia, PA, 1998, vol. 14, pp. 578584.
    12. 12)
    13. 13)
      • 13. Zhang, P., Ding, S.X., Wang, G., Zhou, D.H.: ‘Fault detection in multirate sampled data systems with time delays’. Proc. 2002 IFAC World Congress, Barcelona, Spain, 2002, vol. 16, pp. 33213326.
    14. 14)
    15. 15)
      • 15. Fadali, M., Colaneri, P., Nel, M.: ‘H2 robust fault estimation for periodic systems’. Proc. 2003 American Control Conf., Denver, CO, 2003, vol. 6, pp. 29732978.
    16. 16)
    17. 17)
    18. 18)
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