State estimation for infinite-dimensional systems
Journal of Computer and System Sciences
The innovations approach to space-time filtering and smoothing
Information Sciences: an International Journal
Paper: Estimation of urban air pollution
Automatica (Journal of IFAC)
The experimental implementation of a distributed parameter filter
Automatica (Journal of IFAC)
Paper: Smoothing algorithms for nonlinear distributed parameter systems
Automatica (Journal of IFAC)
Paper: Real time distributed parameter state estimation applied to a two dimensional heated ingot
Automatica (Journal of IFAC)
Correspondence item: Error analysis algorithms for distributed parameter filtering
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
The problem of estimating the state of a class of linear distributed parameter systems from noisy measurements is considered from the viewpoint of weighted least-squares estimation over the spatial domain of the system and the time interval of the measurement data. The problem is reduced to a two-point boundary-value problem via the calculus of variations. The two-point boundary-value problem is then solved in closed form via the sweep method to obtain a Kalman-Bucy type filter. Solution of the smoothing problem then follows directly. Cases are considered where measurement data are obtained over the entire spatial domain of the system or at discrete points in this domain, and where the system is subject to internal and external disturbances as well as measurement errors. Some resulting problems for future study are discussed.