Robust filtering for fault tolerant control using output PDFs of non-Gaussian systems

Y. Zhang; L. Guo; H. Wang

Robust filtering for fault tolerant control using output PDFs of non-Gaussian systems

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Robust filtering for fault tolerant control using output PDFs of non-Gaussian systems

Author(s): Y. Zhang ; L. Guo ; H. Wang
DOI: 10.1049/iet-cta:20050508

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Author(s): Y. Zhang ¹ ; L. Guo ¹ ; H. Wang ²
- Affiliations: 1: College of Automation Engineering, Qingdao University, Qingdao, People's Republic of China
  2: Control Systems Centre, The University of Manchester, Manchester, UK
Source: Volume 1, Issue 3, May 2007, p. 636 – 645
DOI: 10.1049/iet-cta:20050508 , Print ISSN 1751-8644, Online ISSN 1751-8652

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Motivated from some practical industrial processes, an optimal fault tolerant control (FTC) scheme is studied for stochastic continuous dynamic systems with time delays using output probability density functions (PDFs). Different from the classical FTC problems, the measured information is the PDFs of system output rather than its value, where the B-spline expansion technique is applied so that the output PDFs can be formulated in terms of the dynamic weightings. For the established weighting system with nonlinearities, uncertainties and time delays, the concerned FTC problem is investigated by using robust optimisation techniques. A linear matrix inequality (LMI) based feasible FTC method is presented to ensure that the fault can be well estimated and compensated, where the generalised H_∞ performance is optimised for the time-delayed systems with the non-zero initial condition and the truncated norms. Simulations for a model in the paper-making process are given to demonstrate the efficiency of the proposed approach.

References

1. 1)
  - Zhong, M.Y., Ding, S.X., Lam, J., Zhang, C.H.: `Fault detection filter design for LTI system with time-delays', Proc. 42nd IEEE Conf., 2003, Maui, Hawaii, p. 1467–1472.
2. 2)
  - R.J. Patton , J. Chen . (1996) Control and dynamic systems: robust fault detection and isolation (FDI) systems.
3. 3)
  - J.L. Hibey , C.D. Charalambous . Conditional densities for continuous-time nonlinear hybrid systems with applications to fault detection. IEEE Trans. Autom. Control , 2164 - 2170
4. 4)
  - A.A. Stoorvogel , H.H. Niemann , A. Saberi , P. Sannuti . Optimal fault signal estimation. Int. J. Robust Nonlinear Control , 697 - 727
5. 5)
  - Cheng, C., Zhao, Q., Tao, T.: `Stability and performance of the stochastic fault tolerant control systems', Proc. 42nd IEEE CDC, 2003, Denver, CO, USA, p. 2484–2489.
6. 6)
  - L. Xie , C.E. de Souza , M. Fu . H∞ estimation for discrete-time linear uncertain systems. Int. J. Robust Nonlinear Control , 111 - 123
7. 7)
  - L. Guo , H. Wang . Applying constrained nonlinear generalized PI strategy to PDF tracking control through square root B-spline models. Int. J. Control , 17 , 1481 - 1492
8. 8)
  - Wang, H.B., Wang, J.L., Liu, J., Lam, J.: `Iterative LMI approach for robust fault detection observer design', Proc. 42nd IEEE CDC, 2003, Maui, Hawaii, p. 1794–1799.
9. 9)
  - K. Zhou , Z. Ren . A new controller architecture for high performance, robust, and fault-tolerant control. IEEE Trans. Autom. Control , 1613 - 1618
10. 10)
  - X.R. Li , Y. Bar-Shalom . Detection threshold selection for tracking performance optimization. IEEE Trans. Aerosp. Electron. Syst. , 742 - 749
11. 11)
  - R.H. Chen , D.L. Mingori , J.L. Speyer . Optimal stochastic fault detection filter. Automatica , 377 - 390
12. 12)
  - Chen, W., Saif, M.: `Fault detection and accommodation in nonlinear time-delay systems', Proc. ACC, 2003, Maui, Hawaii, p. 4255–4260.
13. 13)
  - L. Guo , H. Wang . Fault detection and diagnosis for general stochastic systems using B-spline expansions and nonlinear filters. IEEE Trans. Circ. Syst. – I: Regular Papers , 8 , 1644 - 1652
14. 14)
  - M. Basseville , I. Nikiforov . Fault isolation for diagnosis: nuisance rejection and multiple hypothesis testing. Ann. Rev. Control , 189 - 202
15. 15)
  - H. Wang , W. Lin . Applying observer based FDI techniques to detect faults in dynamic and bounded stochastic distributions. Int. J. Control , 1424 - 1436
16. 16)
  - J. Liu , J.L. Wang , G.H. Yang . Reliable guaranteed variance filtering against sensor failures. IEEE Trans. Signal Process. , 1403 - 1411
17. 17)
  - Z. Wang , F. Yang . Robust filtering for uncertain linear systems with delayed states and outputs. IEEE Trans. Circ. Syst. – I: Regular Papers , 125 - 130
18. 18)
  - P.M. Frank , S.X. Ding . Survey of robust residual generation and evaluation methods in observer-based fault detection systems. J. Process. Control , 6 , 403 - 424
19. 19)
  - S.Y. Xu , T.W. Chen , J. Lam . Robust H∞ filtering for uncertain Markovian jump systems with mode-dependent time delays. IEEE Trans. Autom. Control , 900 - 907
20. 20)
  - H.J. Gao , J. Lam , L.H. Xie , C.H. Wang . New approach to mixed H2/H∞ filtering for polytopic discrete-time systems. IEEE Trans. Signal Process. , 3183 - 3192
21. 21)
  - R. Isermann , P. Balle . Trends in the application of model based fault detection and diagnosis of technical processes. Control Engineering Practice , 5 , 709 - 719
22. 22)
  - Guo, L., Zhang, Y.-M., Feng, C.-B.: `Generalized ', Proc. 8th Int. Conf. Control, Automation, Robotics and Vision (ICARCV'04), 2004, Kunming, p. 160–165.
23. 23)
  - M. Mufeed , J. Jiang , Y.M. Zhang . Stochastic stability analysis of fault-tolerant control systems in the presence of noise. IEEE Trans. Autom. Control , 11 , 1810 - 1813
24. 24)
  - H. Wang . (2000) Bounded dynamic stochastic systems: modelling and control.
25. 25)
  - P. Li , V. Kadirkamanathan . Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems. IEEE Trans. Syst., Man Cybern.–Part C , 337 - 343

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Robust filtering for fault tolerant control using output PDFs of non-Gaussian systems

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