Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter

Journal of Process Control

Volumn 21, Issue 4, 2011, Pages 585-601

  Bavdekar, Vinay A ^a   Deshpande, Anjali P ^a   Patwardhan, Sachin C ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

Covariance estimation; Expectation maximisation algorithm; Extended Kalman filter; Maximum likelihood estimates; Nonlinear state estimation

Indexed keywords

BAYESIAN; CHARACTERISATION; COVARIANCE ESTIMATION; DECISION VARIABLES; DERIVATIVE-FREE METHODS; EM ALGORITHMS; EXPECTATION-MAXIMISATION; EXPERIMENTAL STUDIES; INNOVATION SEQUENCE; INPUT-OUTPUT DATA; LABORATORY SCALE; LIKELIHOOD FUNCTIONS; MAXIMUM LIKELIHOOD ESTIMATE; MAXIMUM LIKELIHOOD ESTIMATES; MEASUREMENT NOISE; NOISE COVARIANCE; NOISE DENSITY; NONLINEAR STATE ESTIMATION; OBJECTIVE FUNCTIONS; OPTIMISATIONS; SIMULATION RESULT; STATE DYNAMICS; STATE ESTIMATORS; STRUCTURED NOISE; TUNING PARAMETER;

ALGORITHMS; COVARIANCE MATRIX; EXTENDED KALMAN FILTERS; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; POSITION CONTROL; SPURIOUS SIGNAL NOISE; STATE ESTIMATION; UNCERTAINTY ANALYSIS;

PARAMETER ESTIMATION;

EID: 79953818807     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2011.01.001     Document Type: Article

References (25)

1. D. Dochain State and parameter estimation in chemical and biochemical processes: a tutorial J. Process Control 13 2003 801 818
2. J. Rawlings, and B. Bakshi Particle filtering and moving horizon estimation Comput. Chem. Eng. 30 2006 1529 1541 (Pubitemid 44292278)
3. R.J. Fitzgerald Divergence of the Kalman filter IEEE Trans. Automat. Control 16 6 1976 736 747
4. K.A. Myers, and B.D. Tapley Adaptive sequential estimation with unknown noise statistics IEEE Trans. Automat. Control 21 1976 520 523
5. B.J. Odelson, A. Lutz, and J.B. Rawlings The autocovariance-least squares method for estimating covariances: application to model-based control of chemical reactors IEEE Trans. Control Syst. Technol. 14 3 2006 532 540
6. R.K. Mehra On the identification of variances and adaptive Kalman filtering IEEE Trans. Automat. Control 15 12 1970 175 184
7. P.R. Blanger Estimation of noise covariances for a linear time-varying stochastic process Automatica 10 1974 267 275
8. B.J. Odelson, M.R. Rajamani, and J.B. Rawlings A new autocovariance least-squares method for estimating noise covariances Automatica 42 2006 303 308 (Pubitemid 41828190)
9. A.P. Dempster, N.M. Laird, and D. Rubin Maximum likelihood from incomplete data via the EM algorithm J. R. Stat. Soc. B 3 1977 1 38
10. R.H. Shumway, and D.S. Stoffer Time Series Analysis and its Applications 2000 Springer-Verlag New York Inc. New York
11. H. Raghavan, A.K. Tangirala, R.B. Gopaluni, and S.L. Shah Identification of chemical processes with irregular output sampling Control Eng. Pract. 14 2006 467 480 (Pubitemid 43092174)
12. J. Valappil, and C. Georgakis Systematic estimation of state noise statistics for extended Kalman filters AIChE J. 46 2 2000 292 308 (Pubitemid 30110936)
13. G.C. Goodwin, and J.C. Agüero Approximate EM algorithms for parameter and state estimation in nonlinear stochastic models Proc. 44th IEEE Conference on Decision and Control 2005 368 373 (Pubitemid 46296994)
14. S.B. Chitralekha, J. Prakash, H. Raghavan, R.B. Gopaluni, and S.L. Shah A comparison of simultaneous state and parameter estimation schemes for a continuous fermenter J. Process Control 20 8 2010 934 943
15. N.F. Thornhill, S.C. Patwardhan, and S.L. Shah A continuous stirred tank heater simulation J. Process Control 18 3/4 2008 347 360
16. K.R. Muske, and T.F. Edgar M.A. Henson, D.E. Seborg, Nonlinear State Estimation in Nonlinear Process Control 1997 Prentice Hall New Jersey
17. M.S. Arulampalam, S. Maskell, and T. Clapp A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking IEEE Trans. Signal Process. 50 2 2002 174 188 (Pubitemid 34291500)
18. D.M. Himmelblau Process Analysis by Statistical Methods 1970 John Wiley & Sons Inc. New York
19. F.C. Schweppe Evaluation of likelihood functions for Gaussian signals IEEE Trans. Inform. Theory 11 1 1965 61 70
20. H.E. Rauch, F. Tung, and C.T. Striebel Maximum likelihood estimates of linear dynamic systems AIAA J. 3 8 1965 1445 1450
21. G.J. McLachlan, and T. Krishnan The EM Algorithm and Extensions 1997 John Wiley & Sons Inc. New York
22. C.F.J. Wu On the convergence properties of the EM algorithm Ann. Stat. 11 1 1983 95 103
23. M.A. Henson, and D.E. Seborg Nonlinear control strategies for continuous fermenters Chem. Eng. Sci. 47 4 1992 821 835
24. M. Srinivasrao, S.C. Patwardhan, and R.D. Gudi Nonlinear predictive control of irregularly sampled multirate systems using nonlinear black box observers J. Process Control 17 1 2007 17 35 (Pubitemid 44872941)
25. A.P. Deshpande, A unified framework for online fault identification and accommodation in nonlinear systems, Ph.D. thesis, Indian Institute of Technology Bombay, Mumbai, India, 2008.