http://iet.metastore.ingenta.com
1887

Event-based fault detection for non-linear networked systems with multi-data transmission and output quantisation

Event-based fault detection for non-linear networked systems with multi-data transmission and output quantisation

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study is concerned with the event-triggered fault detection (FD) filter design problem for the discrete-time non-linear systems with multi-data transmission and output quantisation. To reduce the transmission data size, the output signals are quantified by a logarithmic quantiser. Compared with the existing results, past output measurements are first introduced for packaging and transmission only when the event condition is satisfied. Based on this consideration, more data can be used by the FD filter, while using the traditional method, the FD filter can only use the current data. Finally, some simulation results show that the proposed design method can achieve a better FD performance than the existing method with current output measurements transmission.

References

    1. 1)
      • 1. Yang, G.H., Wang, H.M.: ‘Fault detection for a class of uncertain state feedback control systems’, IEEE Trans. Control Syst. Technol., 2010, 18, (1), pp. 201212.
    2. 2)
      • 2. Zhou, M.Y., Ding, S.X., Ding, E.L.: ‘Optimal fault detection for linear discrete time-varying systems’, Bul. Inst. Politeh. ‘Gheorghe Gheorghiu-Dej’ Bucur. Ser. Autom., 2010, 46, (8), pp. 13951400.
    3. 3)
      • 3. Dong, H.L., Wang, Z.D., Gao, H.J.: ‘Fault detection for Markovian jump systems with sensor saturations and randomly varying nonlinearities’, IEEE Trans. Circuits Syst. I: Reg. Pap., 2012, 59, (10), pp. 23542362.
    4. 4)
      • 4. Gao, H.J., Li, X.W.: ‘H filtering for discrete-time state-delayed systems with finite frequency specifications’, IEEE Trans. Autom. Control, 2011, 56, (12), pp. 29352941.
    5. 5)
      • 5. Zhuang, G.M., Li, Y.M., Li, Z.: ‘Fault detection for a class of uncertain nonlinear Markovian jump stochastic systems with mode-dependent time delays and sensor saturation’, Int. J. Syst. Sci., 2016, 47, (7), pp. 15141532.
    6. 6)
      • 6. Dong, H.L., Wang, Z.D., Lam, J., et al: ‘Fuzzy-model-based robust fault detection with stochastic mixed time delays and successive packet dropouts’, IEEE Trans. Syst. Man Cybern. B (Cybern.), 2012, 42, (2), pp. 365376.
    7. 7)
      • 7. Li, X.J., Yang, G.H.: ‘Fault detection and isolation for uncertain closed-loop systems based on adaptive and switching approaches’, Int. J. Robust Nonlinear Control, 2016, 26, pp. 29162937.
    8. 8)
      • 8. Li, H.Y., Gao, Y.B., Shi, P., et al: ‘Observer-based fault detection for nonlinear systems with sensor fault and limited communication capacity’, IEEE Trans. Autom. Control, 2016, 61, (9), pp. 27452751.
    9. 9)
      • 9. Cassandras, C.G.: ‘The event-driven paradigm for control, communication and optimization’, J. Control Decis., 2014, 1, (1), pp. 37.
    10. 10)
      • 10. Lehmann, D., Lunze, J.: ‘Extension and experimental evaluation of an event-based state-feedback approach’, Int. J. Robust Nonlinear Control, 2011, 19, (2), pp. 101112.
    11. 11)
      • 11. Zhang, X.M., Han, Q.L.: ‘Event-based H filtering for sampled-data systems’, Bul. Inst. Politeh. ‘Gheorghe Gheorghiu-Dej’ Bucur. Ser. Autom., 2015, 51, pp. 5569.
    12. 12)
      • 12. Zhang, J., Peng, C.: ‘Event-triggered H filtering for networked Takagi–Sugeno fuzzy systems with asynchronous constraints’, IET Signal Process., 2015, 9, (4), pp. 403411.
    13. 13)
      • 13. Wang, H.J., Shi, P., Zhang, J.H.: ‘Event-triggered fuzzy filtering for a class of nonlinear networked control systems’, Analog Integr. Circuits Signal Process., 2015, 113, pp. 159168.
    14. 14)
      • 14. Ge, X.H., Han, Q.L.: ‘Distributed event-triggered H filtering over sensor networks with communication delays’, Int. J. Comput. Inf. Sci., 2015, 291, pp. 128142.
    15. 15)
      • 15. Zhang, J.H., Feng, G.: ‘Event-driven observer-based output feedback control for linear systems’, Automatica, 2014, 50, pp. 18521859.
    16. 16)
      • 16. Zhang, X.M., Han, Q.L.: ‘Event-triggered dynamic output feedback control for networked control systems’, IET Control Theory Appl., 2014, 8, (4), pp. 226234.
    17. 17)
      • 17. Pan, Y.N., Yang, G.H.: ‘Event-triggered fuzzy control for nonlinear networked control systems’, Fuzzy Sets Syst., doi: 10.1016/j.fss.2017.05.010.
    18. 18)
      • 18. Li, Y.X., Yang, G.H.: ‘Model-based adaptive event-triggered control of strict-feedback nonlinear systems’, IEEE Trans. Neural Netw. Learn. Syst., doi: 10.1109/TNNLS.2017.2650238.
    19. 19)
      • 19. Jia, X.C., Chi, X.B., Han, Q.L., et al: ‘Event-triggered fuzzy H control for a class of nonlinear networked control systems using the deviation bounds of asynchronous normalized membership functions’, Inf. Sci., 2014, 259, pp. 100117.
    20. 20)
      • 20. Yan, H.C., Wang, T.T., Zhang, H., et al: ‘Event-triggered H control for uncertain networked T–S fuzzy systems with time delay’, Neurocomputing, 2015, 157, pp. 273279.
    21. 21)
      • 21. Zhang, D.W., Han, Q.L., Jia, X.C.: ‘Network-based output tracking control for T–S fuzzy systems using an event-triggered communication scheme’, Fuzzy Sets Syst., 2015, 273, pp. 2648.
    22. 22)
      • 22. Wang, Y.L., Shi, P., Lim, C.C., et al: ‘Event-triggered fault detection filter design for a continuous-time networked control system’, IEEE Trans. Cybern., 2016, 46, (12), pp. 34143426.
    23. 23)
      • 23. Huong, D.C., Trinh, H., Tran, H.M., et al: ‘Approach to fault detection of time-delay systems using functional observers’, Electron. Lett., 2014, 50, (16), pp. 11321134.
    24. 24)
      • 24. Li, H.Y., Chen, Z., Wu, L.G., et al.: ‘Event-triggered fault detection of nonlinear networked systems’, IEEE Trans. Cybern., 2017, 47, (4), pp. 10411052.
    25. 25)
      • 25. Hajshirmohamadi, S., Davoodi, M., Meskin, N., et al: ‘Event-triggered fault detection and isolation for discrete-time linear systems’, IET Control Theory Appl., 2016, 10, (5), pp. 526533.
    26. 26)
      • 26. Liu, J.L., Yue, D.: ‘Event-based fault detection for networked systems with communication delay and nonlinear perturbation’, J. Franklin Inst., 2013, 350, (9), pp. 27912807.
    27. 27)
      • 27. Wang, Y.L., Lim, C.C., Shi, P.: ‘Adaptively adjusted event-triggering mechanism on fault detection for networked control systems’, IEEE Trans. Cybern., 2017, 47, (8), pp. 22992311.
    28. 28)
      • 28. Zhang, Z.H., Yang, G.H.: ‘Event-triggered fault detection for a class of discrete-time linear systems using interval observers’, ISA Trans., 2017, 68, pp. 160169.
    29. 29)
      • 29. Frezzatto, L., de Oliveira, M.C.C., Oliveira, R.C., et al: ‘Robust H filter design with past output measurements for uncertain discrete-time systems’, Bul. Inst. Politeh. ‘Gheorghe Gheorghiu-Dej’ Bucur. Ser. Autom., 2016, 71, pp. 151158.
    30. 30)
      • 30. Fu, M.Y., Xie, L.H.: ‘The sector bound approach to quantized feedback control’, IEEE Trans. Autom. control, 2005, 50, (11), pp. 16981711.
    31. 31)
      • 31. Nam, P.T., Pathirana, P.N., Trinh, H.: ‘ε-bounded state estimation for time-delay systems with bounded disturbances’, Int. J. Control, 2014, 87, (9), pp. 17471756.
    32. 32)
      • 32. Nguyen, M.C., Trinh, H., Nam, P.T.: ‘Linear functional observers with guaranteed ε-convergence for discrete time-delay systems with input/output disturbances’, Int. J. Syst. Sci., 2016, 47, (13), pp. 31933205.
    33. 33)
      • 33. Wang, Z., Yang, F., Ho, D., et al: ‘Robust H filtering for stochastic time-delay systems with missing measurements’, IEEE Trans. Signal Process., 2006, 54, (7), pp. 25792587.
    34. 34)
      • 34. Boyd, S., Ghaoui, L.E., Feron, E., et al.: ‘Linear matrix inequalities in system and control theory’ (SIAM, Philadelphia, PA, USA, 1994).
    35. 35)
      • 35. Wang, H., Yang, G.H.: ‘A finite frequency domain approach to fault detection for linear discrete-time systems’, Int. J. Control, 2008, 81, (7), pp. 11621171.
    36. 36)
      • 36. Wei, Q.L., Liu, D.R., Yang, X.: ‘Infinite horizon self-learning optimal control of nonaffine discrete-time nonlinear systems’, IEEE Trans. Neural Netw. Learn. Syst., 2015, 26, (4), pp. 866879.
    37. 37)
      • 37. Dong, H.L., Bu, X.Y., Hou, N., et al: ‘Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels’, Inf. Fusion, 2017, 36, pp. 243250.
    38. 38)
      • 38. Dong, H.L., Wang, Z.D., Shen, B., et al.: ‘Variance-constrained H control for a class of nonlinear stochastic discrete time-varying systems: the event-triggered design’, Automatica, 2016, 72, pp. 2836.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2017.0293
Loading

Related content

content/journals/10.1049/iet-cta.2017.0293
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address