Bayesian estimation via sequential Monte Carlo sampling-Constrained dynamic systems

Automatica

Volumn 43, Issue 9, 2007, Pages 1615-1622

  Lang, Lixin ^b   Chen, Wen shiang ^a   Bakshi, Bhavik R ^a   Goel, Prem K ^b   Ungarala, Sridhar ^c  

^a The Ohio State University   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c Cleveland State University   (United States)

Author keywords

Constrained estimation; Data rectification; Extended Kalman filter; Moving horizon estimation; Particle filter

Indexed keywords

CONSTRAINED OPTIMIZATION; DATA REDUCTION; DYNAMICAL SYSTEMS; GAUSSIAN DISTRIBUTION; KALMAN FILTERS; MONTE CARLO METHODS;

CONSTRAINED ESTIMATION; EXTENDED KALMAN FILTER; MOVING HORIZON ESTIMATION; PARTICLE FILTER;

BAYESIAN NETWORKS;

EID: 34547583106     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2007.02.012     Document Type: Article

References (20)

1. Arulampalam M.S., Maskell S., Gordon N., and Clapp T. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing 50 2 (2002) 174-188
2. Chaves M., and Sontag E.D. State-estimator for chemical reaction networks of Feinberg-Horn-Jackson zero deficiency type. European Journal of Control 8 4 (2002) 343-359
3. Chen W.-S., Bakshi B.R., Goel P.K., and Ungarala S. Bayesian estimation of unconstrained nonlinear dynamic systems via sequential Monte Carlo sampling. Industrial & Engineering Chemistry Research 43 14 (2004) 4012-4025
4. Crisan D. Particle filters-A theoretical perspective. In: Doucet A., de Freitas N., and Gordon N. (Eds). Sequential Monte Carlo methods in practice (2001), Springer, New York 17-41 (Chapter 2)
5. Crisan D., and Doucet A. A survey of convergence results on particle filtering methods for practitioners. IEEE Transactions on Signal Processing 50 3 (2002) 736-746
6. Del Moral P., and Miclo L. Branching and interacting particles systems. Approximations of feynman-kac formulae with applications to non-linear filtering. Séminaire de Probabilitités XXXIV. Lecture notes in mathematics (2000), Springer, Berlin 1-145
7. Doucet A., Godsill S., and Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing 10 (2000) 197-208
8. Geweke J. Bayesian inference in econometric models using Monte Carlo integration. Econometrica 57 6 (1989) 1317-1339
9. Gordon N.J., Salmond D.J., and Smith A.F.M. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings-F 140 2 (1993) 107-113
10. Haseltine E.L., and Rawlings J.B. Critical evaluation of extended Kalman filtering and moving-horizon estimation. Industrial & Engineering Chemistry Research 44 (2005) 2451-2460
11. Henson M.A., and Seborg D.E. Nonlinear process control (1997), Prentice-Hall PTR, Upper Saddle River, NJ
12. Jang S.-S., Joseph B., and Mukai H. Comparison of two approaches to on-line parameter and state estimation of nonlinear systems. Industrial and Engineering Chemistry Process Design and Development 25 (1986) 809-814
13. Jazwinski A.H. Stochastic processes and filtering theory (1970), Academic Press, New York
14. Julier S.J., and Uhlmann J.K. Unscented filtering and nonlinear estimation. Proceedings of IEEE 92 3 (2004) 401-422
15. Künsch H.R. Recursive Monte Carlo filters: algorithms and theoretical analysis. Annals of Statistics 33 5 (2005) 1983-2021
16. Lang, L., Chen, W.-S., Bakshi, B. R., Goel, P. K., & Ungarala, S. (2006). Bayesian rectification via sequential Monte Carlo sampling of constrained systems. Technical Report, Ohio State University.
17. McKeithan T.W. Kinetic proofreading in t-cell receptor signal transduction. Proceedings of the national academy of sciences 92 (1995) 5042-5046
18. Robertson D.G., Lee J.H., and Rawlings J.B. A moving horizon-based approach for least-squares estimation. AIChE Journal 42 8 (1996) 2209-2224
19. Tenny, M. J. (2002). Computational strategies for nonlinear model predictive control. Ph.D. thesis, University of Wisconsin-Madison.
20. Ungarala S., and Bakshi B.R. Multiscale Bayesian estimation and data rectification. In: Petrosian A.A., and Meyer F.G. (Eds). Wavelets in signal and image analysis (2001), Kluwer, The Netherlands 69-110