Reply to Comments on "Robust and reliable estimation via unscented recursive nonlinear dynamic data reconciliation" (URNDDR)

Journal of Process Control

Volumn 19, Issue 4, 2009, Pages 719-721

  Narasimhan, Shankar ^a   Rengaswamy, Raghunathan ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

^b Wallace H Coulter School of Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 63249131100     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2008.08.002     Document Type: Letter

References (6)

1. Vachhani P., Narasimhan S., and Rengaswamy R. Robust and reliable estimation via unscented recursive nonlinear dynamic data reconciliation. Journal of Process Control 16 (2006) 1075-1086
2. Burgers G., Leeuwen P.J.V., and Evensen G. Analysis scheme in the ensemble Kalman filter. Monthly Weather Review 126 (1998) 1719-1724
3. Whitaker J.S., and Hamill T.M. Ensemble data assimilation without perturbed observations. Monthly Weather Review 130 (2002) 1913-1924
4. Raissouli M., and Leazizi F. Continued fraction expansion of the geometric matrix mean and applications. Linear Algebra and its Applications 359 (2003) 37-57
5. Prakash J., Patwardhan S.C., and Shah S.L. Constrained state estimation using the ensemble Kalman filter. American Control Conference (2008) 3542-3547
6. Prakash J., Patwardhan S.C., and Shah S.L. Constrained state estimation using particle filters, IFAC. World Congress, Seoul (2008) 6472-6477