Ensemble-based simultaneous input and state estimation for nonlinear dynamic systems with application to wildfire data assimilation

[1]  E. Robinson.  PREDICTIVE DECOMPOSITION OF SEISMIC TRACES , 1957 .

[2]  B. Friedland.  Treatment of bias in recursive filtering , 1969 .

[3]  C. E. Van Wagner,et al.  Conditions for the start and spread of crown fire , 1977 .

[4]  J. Mendel.  White-noise estimators for seismic data processing in oil exploration , 1977 .

[5]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Jack D. Cohen,et al.  The 1978 National Fire-Danger Rating System: technical documentation , 1984 .

[7]  Peter K. Kitanidis,et al.  Unbiased minimum-variance linear state estimation , 1987, Autom..

[8]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[9]  G. Evensen.  Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[10]  Mohamed Darouach,et al.  Unbiased minimum variance estimation for systems with unknown exogenous inputs , 1997, Autom..

[11]  J. Gentle.  Random number generation and Monte Carlo methods , 1998 .

[12]  M. Finney.  FARSITE : Fire Area Simulator : model development and evaluation , 1998 .

[13]  Martin J. Corless,et al.  State and Input Estimation for a Class of Uncertain Systems , 1998, Autom..

[14]  R. M. Nelson,et al.  Prediction of diurnal change in 10-h fuel stick moisture content , 2000 .

[15]  Chien-Shu Hsieh,et al.  Robust two-stage Kalman filters for systems with unknown inputs , 2000, IEEE Trans. Autom. Control..

[16]  Kazufumi Ito,et al.  Gaussian filters for nonlinear filtering problems , 2000, IEEE Trans. Autom. Control..

[17]  X. Rong Li,et al.  A Survey of Maneuvering Target Tracking—Part IV: Decision-Based Methods , 2002 .

[18]  Mohamed Darouach,et al.  Extension of minimum variance estimation for systems with unknown inputs , 2003, Autom..

[19]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[20]  Hieu Minh Trinh,et al.  State and input simultaneous estimation for a class of nonlinear systems , 2004, Autom..

[21]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[22]  H. Kobayashi,et al.  Disturbance estimation and rejection - an equivalent input disturbance estimator approach , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[23]  A. Gut.  Probability: A Graduate Course , 2005 .

[24]  M. Buehner,et al.  Atmospheric Data Assimilation with an Ensemble Kalman Filter: Results with Real Observations , 2005 .

[25]  Istvan Szunyogh,et al.  Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter , 2005, physics/0511236.

[26]  Miguel Ayala Botto,et al.  Simultaneous state and input estimation of hybrid systems with unknown inputs , 2006, Autom..

[27]  E. Lorenz.  Predictability of Weather and Climate: Predictability – a problem partly solved , 2006 .

[28]  K. Ide,et al.  A Method for Assimilating Lagrangian Data into a Shallow-Water-Equation Ocean Model , 2006 .

[29]  G. Evensen.  Data Assimilation: The Ensemble Kalman Filter , 2006 .

[30]  T. Floquet,et al.  On Sliding Mode Observers for Systems with Unknown Inputs , 2006, International Workshop on Variable Structure Systems, 2006. VSS'06..

[31]  Bart De Moor,et al.  Unbiased minimum-variance input and state estimation for linear discrete-time systems , 2007, Autom..

[32]  Bart De Moor,et al.  Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough , 2007, Autom..

[33]  R. Ibbitt,et al.  Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model , 2007 .

[34]  L. Fridman,et al.  Exact state estimation for linear systems with unknown inputs based on hierarchical super‐twisting algorithm , 2007 .

[35]  Jingang Yi,et al.  A new algorithm for simultaneous input and state estimation , 2008, 2008 American Control Conference.

[36]  T. DelSole,et al.  Using the ensemble Kalman filter to estimate multiplicative model parameters , 2008 .

[37]  Fuli Wang,et al.  Hybrid Estimation of State and Input for Linear Discrete Time-varying Systems: A Game Theory Approach , 2008 .

[38]  Albert C. Reynolds,et al.  Iterative Ensemble Kalman Filters for Data Assimilation , 2009 .

[39]  Donghua Zhou,et al.  Unbiased minimum-variance state estimation for linear systems with unknown input , 2009, Autom..

[40]  James V. Candy,et al.  Bayesian Signal Processing: Classical, Modern and Particle Filtering Methods , 2009 .

[41]  Minjeong Kim,et al.  Data assimilation for wildland fires , 2007, IEEE Control Systems.

[42]  Dongbin Xiu,et al.  A generalized polynomial chaos based ensemble Kalman filter with high accuracy , 2009, J. Comput. Phys..

[43]  Christian P. Robert,et al.  Introducing Monte Carlo Methods with R , 2009 .

[44]  Eugenia Kalnay,et al.  Ensemble Kalman Filter: Current Status and Potential , 2010 .

[45]  Chien-Shu Hsieh.  On the optimality of two‐stage Kalman filtering for systems with unknown inputs , 2010 .

[46]  Huazhen Fang,et al.  Nonlinear simultaneous input and state estimation with application to flow field estimation , 2011, IEEE Conference on Decision and Control and European Control Conference.

[47]  Jingang Yi,et al.  On stable simultaneous input and state estimation for discrete‐time linear systems , 2011 .

[48]  Udo Schubert,et al.  Input reconstruction for statistical‐based fault detection and isolation , 2012 .

[49]  Anton J. Haug.  Bayesian Estimation and Tracking: A Practical Guide , 2012 .

[50]  Huazhen Fang,et al.  On the asymptotic stability of minimum-variance unbiased input and state estimation , 2012, Autom..

[51]  Chien-Shu Hsieh.  A unified framework for state estimation of nonlinear stochastic systems with unknown inputs , 2013, 2013 9th Asian Control Conference (ASCC).

[52]  Huazhen Fang,et al.  Simultaneous input and state smoothing and its application to oceanographic flow field reconstruction , 2013, 2013 American Control Conference.

[53]  Huazhen Fang,et al.  Simultaneous input and state estimation for nonlinear systems with applications to flow field estimation , 2013, Autom..

[54]  Henry D. I. Abarbanel,et al.  Predicting the Future: Completing Models of Observed Complex Systems , 2013 .

[55]  Roshan A. Chavan,et al.  Recursive input reconstruction with a delay , 2014, 2014 American Control Conference.

[56]  Andrew J. Majda,et al.  Ensemble Kalman filters for dynamical systems with unresolved turbulence , 2014, J. Comput. Phys..

[57]  Andrew J. Majda,et al.  An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models , 2014, J. Comput. Phys..

[58]  Huazhen Fang,et al.  Simultaneous input and state filtering: An ensemble approach , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[59]  Huazhen Fang,et al.  Smoothed estimation of unknown inputs and states in dynamic systems with application to oceanic flow field reconstruction , 2015 .

[60]  A. Stuart,et al.  Data Assimilation: A Mathematical Introduction , 2015, 1506.07825.

[61]  Alison Fowler.  The Ensemble Kalman filter , 2016 .

[62]  Emilio Frazzoli,et al.  A unified filter for simultaneous input and state estimation of linear discrete-time stochastic systems , 2013, Autom..

[63]  R. Rothermel.  A Mathematical Model for Predicting Fire Spread in Wildland Fuels , 2017 .

[64]  R. Rothermel,et al.  Predicting Behavior and Size of Crown Fires in the Northern Rocky Mountains , 2018 .