State Estimation over Customized Wireless Network

Sayed Vahid Naghavi, Ali Azami, Freidoon Shabaninia

School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran..
Young Researchers Club, Zarghan Branch, Islamic Azad University, Zarghan, Iran;.

DOI: 10.4236/wet.2012.34032                

Abstract

In this paper the state estimation techniques are investigated over customized wireless network for a continuous-time plant. It is assumed that the plant is connected to the controller over the proposed network. The feedback control over wireless networks includes limited bandwidth, time-varying and unknown delays with a high probability of data loss. Reasonably, some of these issues are deduced from the wireless networks structures. In order to deal with these problems the customized wireless network architecture is proposed for this Wireless Networked Control System (WNCS) and the problem of transmission delays and packet losses which induced by this scheme is studied. The time-varying delays of the TCP based shared network is estimated by fuzzy state estimation technique. Thereafter the kalman filtering is applied to address the problem of optimal filtering for this continuous-time plant with time-varying delays. The re-organized innovation analysis approach is applied to tackle the network induced time-varying delays. The simulation results show the applicability of the proposed approach.

Keywords

Estimation; Customized Wireless Network; Kalman Filtering; Time Varying Delay

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	J. P. Hespanha, P. Naghshtabrizi and Y. Xu, “A Survey of Recent Results in Networked Control Systems,” IEEE Transactions on Automatic Control, Vol. 95, No. 1, pp. 138-162, 2007.
[2]	Rachana Ashok Gupta and Mo-Yuen Chow, “Networked Control System: Overview and Research Trends,” IEEE Transactions on Industrial Electronics, Vol. 57, No. 7, 2010, pp. 2527-2535.
[3]	F. Shabaninia, “A Fuzzy-Logic-Supported Weighted Least Squares State Estimation,” Electric Power Systems Research Journal, Vol. 39. No. 1, 1996, pp. 55-60.
[4]	F. Shabaninia, “State Estimation with Aid of Fuzzy Logic,” Proceeding of FUZZ-IEEE’96 Conference, Baton Rouge, 8-11 September 1996, pp. 947-952.
[5]	M. Sahebsara, T. Chen and S. L. Shah, “Optimal H2 filtering with Random Sensor Delay, Multiple Packet Dropout and Uncertain Observations,” International Journal of Control, Vol. 80, No. 2, 2007, pp. 292-301.
[6]	S. Sun, L. Xie, W. Xiao and Y. C. Soh, “Optimal Linear Estimation for Systems with Multiple Packet Dropouts,” Automatica, Vol. 44, No. 5, 2008, pp. 1333-1342. doi:10.1016/j.automatica.2007.09.023
[7]	M. Moayedi, Y. C. Soh and Y. K. Foo, “Optimal Kalman Filtering with Random Sensor Delays, Packet Dropouts and Missing Measurements,” Proceedings of American Control Conference, St. Louis, 10-12 June 2009, pp. 3405-3410.
[8]	H. S. Zhang, L. H. Xie, D. Zhang and Y. C. Soh, “A re-Organized Innovation Approach to Linear Estimation,” IEEE Transactions on Automatic Control, Vol. 49, No. 10, 2004, pp. 1810-1814. doi:10.1109/TAC.2004.835599
[9]	W. Wang, H. Zhang and L. Xie, “Kalman Filtering for Continuous-Time Systems with Time-Varying Delay,” IET Control, Vol. 28, No. 4, 2009, pp. 590-600.