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

Control and decision strategy for a class of Markovian jump systems in failure prone manufacturing process

Control and decision strategy for a class of Markovian jump systems in failure prone manufacturing process

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 investigates control and decision strategy for the failure prone manufacturing process, which is modelled as a two-mode Markovian jump system (MJS). Considering the historical effects on the system, the mode transition rate matrix (MTRM) is time-varying instead of homogeneous. A piecewise homogeneous MJS is thus proposed to characterise this phenomenon, in which the MTRM is homogeneous during certain time intervals but non-homogeneous for the whole time interval. By regarding each homogeneous MTRM as one event, all the MTRMs over the whole time interval will take values in an event set and be governed by a higher-level Markov chain. To ensure such system operates normally with high probability, the decisions including preventive maintenance and corrective maintenance are introduced to adjust the higher-level Markov chain. Motivated by this, a new joint performance, consisting of both cost function for decision making and controller design, is developed. Optimal decisions are obtained by an iterative algorithm whose convergence is proved, as well as an optimal controller is designed. The effectiveness of this method is demonstrated by simulations.

References

    1. 1)
      • C.G. Cassandras , S. Lafortune . (1999) Introduction to discrete event systems.
    2. 2)
      • M. Mariton . (1990) Jump linear systems in automatic control.
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
      • Zhang, L.X.: ` control of a class of piecewise homogeneous Markov jump linear systems', Proc. Seventh Asian Control Conf., August 2009, Hong Kong, China, p. 197–202.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • D.W. Stroock . (2005) An introduction to Markov processes.
    20. 20)
    21. 21)
    22. 22)
    23. 23)
    24. 24)
      • Abou-Kandkil, H., Smet, O.D., Freiling, G., Jank, G.: `Flow control in a failure-prone multi-machine manufacturing system', Proc. INRIA/IEEE Symp. Emerging Technologies and Factory Automation, October 1995, Paris, France, p. 575–583.
    25. 25)
    26. 26)
    27. 27)
    28. 28)
    29. 29)
      • S.P. Sethi , Q. Zhang . (1994) Hierarchical decision making in stochastic manufacturing systems.
    30. 30)
      • G. Yin , Q. Zhang . (1996) Recent advances in control and optimization of manufacturing system.
    31. 31)
      • D.P. Bertsekas . (1999) Nonlinear programming.
    32. 32)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2011.0302
Loading

Related content

content/journals/10.1049/iet-cta.2011.0302
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address