Markov chain model of fault-tolerant wireless networked control systems

Article
  • 48 Downloads

Abstract

Wireless networked control systems (WNCS) are composed of spatially distributed sensors, actuators, and controllers communicating through wireless networks instead of conventional point-to-point wired connections. While WNCSs have a tremendous potential to improve the efficiency of many critical control systems, for instance, in building automation and process control, the systems are fundamentally constrained by the packet losses and the functional faults of the underlying wireless sensor and actuator networks. Understanding the interaction between wireless networks and control systems is essential to characterize the performance limitations of the critical control systems and optimize its wireless network resources. This paper presents an analytical framework for modeling the behavior of the control loop over lossy and faulty network. The control loop over wireless networks is modeled through a Markov chain taking into account sensing links, actuating links, and recovery mechanism to compensate the faulty nodes. By using this model, the novel performance metrics are mathematically derived and are evaluated through both theoretical analysis and simulation results. The performance evaluation shows the critical tradeoff between the average performance when the control loop is in the normal operation mode and the recovery performance when it is in the abnormal operating mode due to the faulty nodes.

Keywords

Wireless sensor and actuator network Wireless networked control system Fault-tolerant Packet loss 

References

  1. 1.
    Sztipanovits, J., Koutsoukos, X., Karsai, G., Kottenstette, N., Antsaklis, P., Gupta, V., et al. (2012). Toward a science of cyber–physical system integration. Proceedings of the IEEE, 100(1), 2944.CrossRefGoogle Scholar
  2. 2.
    Bello, O., & Zeadally, S. (2016). Intelligent device-to-device communication in the internet of things. IEEE Systems Journal, 10(3), 11721182.CrossRefGoogle Scholar
  3. 3.
    Hespanha, J. P., Naghshtabrizi, P., & Xu, Y. (2007). A survey of recent results in networked control systems. Proceedings of the IEEE, 95(1), 138162.CrossRefGoogle Scholar
  4. 4.
    Kim, K. D., & Kumar, P. R. (2012). Cyber physical systems: A perspective at the centennial. Proceedings of the IEEE, 100, 12871308.Google Scholar
  5. 5.
    Al-Dabbagh, A. W., & Chen, T. (2016). Design considerations for wireless networked control systems. IEEE Transactions on Industrial Electronics, 63, 5547–5557.CrossRefGoogle Scholar
  6. 6.
    Petersen, S., & Carlsen, S. (2011). WirelessHART versus ISA100.11a: The format war hits the factory floor. IEEE Industrial Electronics Magazine, 5(4), 2334.CrossRefGoogle Scholar
  7. 7.
    Bill, P., Kranich, M., & Chari, N. (2013). Fine mesh 802.11 wireless network connectivity. ABB, Technical reportGoogle Scholar
  8. 8.
    Blaney, J. (2009). Wireless proves its value. Power Engineering, 113(2), 38.Google Scholar
  9. 9.
    Pister, K., Thubert, P., Systems, C., Dwars, S., & Phinney, T. (2009). Industrial routing requirements in low-power and lossy networks. IETF.Google Scholar
  10. 10.
    Bahramgiri, M., Hajiaghayi, M., & Mirrokni, V. S. (2006). Fault-tolerant and 3-dimensional distributed topology control algorithms in wireless multi-hop networks. Wireless Networks, 12(2), 179188.CrossRefGoogle Scholar
  11. 11.
    Thallner, B., Moser, H., & Schmid, U. (2010). Topology control for fault-tolerant communication in wireless ad hoc networks. Wireless Networks, 16(2), 387404.CrossRefGoogle Scholar
  12. 12.
    Saha, I., Sambasivan, L. K., Ghosh, S. K., & Patro, R. K. (2010). Distributed fault-tolerant topology control in wireless multi-hop networks. Wireless Networks, 16(6), 15111524.CrossRefGoogle Scholar
  13. 13.
    Azharuddin, M., & Jana, P. K. (2015). A distributed algorithm for energy efficient and fault tolerant routing in wireless sensor networks. Wireless Networks, 21(1), 251267.CrossRefGoogle Scholar
  14. 14.
    Kwon, K., Kim, S. H., Ha, M., & Kim, D. (2016). Traffic-aware stateless multipath routing for fault-tolerance in IEEE 802.15.4 wireless mesh networks. Wireless Networks.  https://doi.org/10.1007/s11276-016-1427-4.Google Scholar
  15. 15.
    Patankar, R. P. (2004). A model for fault-tolerant networked control system using TTP/C communication. IEEE Transactions on Vehicular Technology, 53(5), 14611467.CrossRefGoogle Scholar
  16. 16.
    Pajic, M., Chernoguzov, A., & Mangharam, R. (2013). Robust architectures for embedded wireless network control and actuation. ACM Transactions on Embedded Computing Systems, 11(4), 82–182.Google Scholar
  17. 17.
    Xiong, J., & Lam, J. (2009). Stabilization of networked control systems with a logic ZOH. IEEE Transactions on Automatic Control, 54(2), 358363.MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Heemels, W. P. M. H., Teel, A. R., van de Wouw, N., & Nesic, D. (2010). Networked control systems with communication constraints: Tradeoffs between transmission intervals, delays and performance. IEEE Transactions on Automatic Control, 55(8), 17811796.MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Rabi, M., Stabellini, L., Proutiere, A., & Johansson, M. (2010). Networked estimation under contention-based medium access. International Journal of Robust and Nonlinear Control, 20(2), 140–155.MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Schenato, L., Sinopoli, B., Franceschetti, M., Poola, K., & Sastry, S. (2007). Foundations of control and estimation over lossy networks. Proceedings of the IEEE, 95(1), 163–187.CrossRefGoogle Scholar
  21. 21.
    Srinivasan, K., Kazandjieva, M. A., Agarwal, S., & Levis, P. (2008). The beta-factor: Measuring wireless link burstiness. In ACM SenSys.Google Scholar
  22. 22.
    Srinivasan, K., Jain, M., Choi, J. I., Azim, T., Kim, E. S., Levis, P., & Krishnamachari, B. (2010). The kappa factor: Inferring protocol performance using inter-link reception correlation. In ACM MobiCom.Google Scholar
  23. 23.
    IEEE Standard for Local and metropolitan area networks—Part 15.4: Low-rate wireless personal area networks (LR-WPANs) amendment 1: MAC sublayer. In IEEE Std 802.15.4e-2012 (Amendment to IEEE Std 802.15.4-2011) (pp. 1–225) (2012).Google Scholar
  24. 24.
    Scheible, G., Dzung, D., Endresen, J., & Frey, J. E. (2007). Unplugged but connected design and implementation of a truly wireless real-time sensor/actuator interface. IEEE Industrial Electronics Magazine, 1(2), 25–34.CrossRefGoogle Scholar
  25. 25.
    Jentzen, A., Leber, F., Schneisgen, D., Berger, A., & Siegmund, S. (2010). An improved maximum allowable transfer interval for IP-stability of networked control systems. IEEE Transactions on Automatic Control, 55(1), 179184.CrossRefMATHGoogle Scholar
  26. 26.
    Sadi, Y., Ergen, S. C., & Park, P. (2014). Minimum energy data transmission for wireless networked control systems. IEEE Transactions on Wireless Communications, 13(4), 21632175.CrossRefGoogle Scholar
  27. 27.
    Park, P. (2015). Traffic generation rate control of wireless sensor and actuator networks. IEEE Communications Letters, 19(5), 827830.CrossRefGoogle Scholar
  28. 28.
    Fridman, E. (2014). Introduction to time-delay systems: analysis and control. Basel: Birkhäuser.CrossRefMATHGoogle Scholar
  29. 29.
    Billinton, R., & Allan, R. (1992). Reliability evaluation of engineering systems: Concepts and techniques. New York, NY: Plenum Press.CrossRefMATHGoogle Scholar
  30. 30.
    Grinstead, C. M., & Snell, J. L. (1998). Introduction to probability. Providence, RI: American Mathematical Society.MATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Radio and Information Communications EngineeringChungnam National UniversityDaejeonKorea

Personalised recommendations