Kalman filtering with unknown inputs via optimal state estimation of singular systems
- 1 October 1995
- journal article
- research article
- Published by Taylor & Francis in International Journal of Systems Science
- Vol. 26 (10) , 2015-2028
- https://doi.org/10.1080/00207729508929152
Abstract
A new method to design a Kalman filter for linear discrete-time systems with unknown inputs is presented. The algorithm recently developed for stochastic singular systems is applied to obtain a linear estimation of the state and unknown inputs. The necessary and sufficient conditions for the existence and stability of the filter are derived and proved. An illustrative example is included.Keywords
This publication has 14 references indexed in Scilit:
- Kalman filtering and Riccati equations for descriptor systemsIEEE Transactions on Automatic Control, 1992
- Design of observers for linear systems with unknown inputsIEEE Transactions on Automatic Control, 1992
- A novel approach to the design of unknown input observersIEEE Transactions on Automatic Control, 1991
- Robust adaptive Kalman filtering with unknown inputsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- Observers for linear systems with unknown inputsIEEE Transactions on Automatic Control, 1988
- Riccati equations in optimal filtering of nonstabilizable systems having singular state transition matricesIEEE Transactions on Automatic Control, 1986
- Stochastic Modelling and ControlPublished by Springer Nature ,1985
- Application of state estimation to target trackingIEEE Transactions on Automatic Control, 1984
- Adaptive sequential estimation with unknown noise statisticsIEEE Transactions on Automatic Control, 1976
- Observing the states of systems with unmeasurable disturbancesIEEE Transactions on Automatic Control, 1975