
Accession Number : AD0696277
Title : LEASTSQUARES FILTERING AND SMOOTHING FOR LINEAR DISTRIBUTED PARAMETER SYSTEMS,
Corporate Author : BOEING SCIENTIFIC RESEARCH LABS SEATTLE WASH INFORMATION SCIENCES LAB
Personal Author(s) : Meditch,J. S.
Report Date : AUG 1969
Pagination or Media Count : 24
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 leastsquares estimation over the spatial domain of the system and the time interval of the measurement data. The problem is reduced to a twopoint boundaryvalue problem via the calculus of variations. The twopoint boundaryvalue problem is then solved in closed form via the sweep method to obtain a KalmanBucy 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)
Descriptors : (*LEAST SQUARES METHOD, INFORMATION THEORY), (*INFORMATION THEORY, *CONTROL SYSTEMS), BOUNDARY VALUE PROBLEMS, CALCULUS OF VARIATIONS, NOISE(RADIO), LINEAR SYSTEMS
Subject Categories : Statistics and Probability
Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE