LEAST-SQUARES FILTERING AND SMOOTHING FOR LINEAR DISTRIBUTED PARAMETER SYSTEMS,
Abstract
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. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1969
- Accession Number
- AD0696277
Entities
People
- J. S. Meditch
Organizations
- Boeing