Bayesian estimation via sequential Monte Carlo sampling-Constrained dynamic systems

DOI10.1016/j.automatica.2007.02.012zbMath1128.93387OpenAlexW2080973322MaRDI QIDQ2466922

Wen-Shiang Chen, Prem K. Goel, Sridhar Ungarala, Bhavik R. Bakshi, Lixin Lang

Publication date: 16 January 2008

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2007.02.012

zbMATH Keywords

extended Kalman filterparticle filterconstrained estimationmoving horizon estimationdata rectification

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Sequential statistical analysis (62L10)

Related Items (9)

Approximate Bayesian Prediction Using State Space Model with Uniform Noise ⋮ Unnamed Item ⋮ Truncation nonlinear filters for state estimation with nonlinear inequality constraints ⋮ Stability analysis for switched discrete-time linear singular systems ⋮ Constrained dynamic systems estimation based on adaptive particle filter ⋮ Convex saturated particle filter ⋮ Bayesian estimation via sequential Monte Carlo sampling-Constrained dynamic systems ⋮ A cubatureH_∞filter and its square-root version ⋮ Stability Analysis of Implicit Difference Equations Under Restricted Perturbations

Cites Work

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• Recursive Monte Carlo filters: algorithms and theoretical analysis
• Bayesian estimation via sequential Monte Carlo sampling-Constrained dynamic systems
• State-estimators for chemical reaction networks of Feinberg-Horn-Jackson zero deficiency type
• Stochastic processes and filtering theory
• Bayesian Inference in Econometric Models Using Monte Carlo Integration
• A survey of convergence results on particle filtering methods for practitioners

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