Continuous-time norm-constrained Kalman filtering

This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two s...

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Bibliographic Details
Published in:Automatica (Oxford) 2014-10, Vol.50 (10), p.2546-2554
Main Authors: Forbes, James Richard, de Ruiter, Anton H.J., Zlotnik, David Evan
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Constraints
Control theory. Systems
Exact sciences and technology
Extended Kalman filters
Fundamental areas of phenomenology (including applications)
Kalman filters
Modelling and identification
Physics
Solid dynamics (ballistics, collision, multibody system, stabilization...)
Solid mechanics
State estimation
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Summary:This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two separate optimization problems, one which solves for the optimal observer gain associated with the unconstrained state estimates, while the other solves for the optimal observer gain associated with the constrained state estimates. The optimal constrained state estimate is found by projecting the time derivative of an unconstrained estimate onto the tangent space associated with the norm constraint. The special case where the entire state estimate is norm-constrained is briefly discussed. The utility of the filtering results developed are highlighted through a spacecraft attitude estimation example. Numerical simulation results are included.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2014.08.007