Analysis of the Kalman filter based estimation algorithm: An orthogonal decomposition approach.
From MaRDI portal
Publication:1426255
DOI10.1016/J.AUTOMATICA.2003.07.011zbMath1035.93063OpenAlexW2028641788MaRDI QIDQ1426255
Publication date: 14 March 2004
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2003.07.011
Filtering in stochastic control theory (93E11) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)
Related Items (3)
Stationary behavior of an anti-windup scheme for recursive parameter estimation under lack of excitation ⋮ Recursive parameter estimation algorithm for multivariate output-error systems ⋮ Elementwise decoupling and convergence of the Riccati equation in the SG algorithm
Cites Work
- Unnamed Item
- Adaptation and tracking in system identification - a survey
- Exponential convergence of recursive last squares with exponential forgetting factor
- Convergence and exponential convergence of identification algorithms with directional forgetting factor
- Problems of identification and control
- A Decomposition Method for Positive Semidefinite Matrices and Its Application to Recursive Parameter Estimation
- Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergence
- Matrix Analysis
- Modified least squares algorithm incorporating exponential resetting and forgetting
- Recursive least-squares identification algorithms with incomplete excitation: convergence analysis and application to adaptive control
- Recursive forgetting algorithms
- Exponential stability of general tracking algorithms
- Performance analysis of general tracking algorithms
- A directional forgetting algorithm based on the decomposition of the information matrix
This page was built for publication: Analysis of the Kalman filter based estimation algorithm: An orthogonal decomposition approach.
