
Accession Number : AD0739606
Title : Kalman Filtering and Quasilinearization, A Comparative Discussion of Two Procedures for Parameter Estimation,
Corporate Author : RENSSELAER POLYTECHNIC INST TROY N Y SYSTEMS ENGINEERING DIV
Personal Author(s) : Kaufman,Howard
Report Date : 1972
Pagination or Media Count : 14
Abstract : Two techniques which have had wide application in the identification of system parameters are Kalman filtering and quasilinearization. This paper discusses the quantitative differences between these two procedures and shows that corresponding estimates will be identical provided that the Kalman estimation is performed with the following restrictions: The state vector about which the process equations are linearized is the solution to the state equations containing the smoothed parameter and initial condition estimates computed at the end of the last data cycle. No updating of this trajectory should be performed as the data is serially processed. At some time after the start of the data record the recursive equations should be initialized with the parameter and state estimates which correspond to a least squares curve fit of the data up to that time. (Author)
Descriptors : (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), PARTIAL DIFFERENTIAL EQUATIONS, MATRICES(MATHEMATICS), RECURSIVE FUNCTIONS, LEAST SQUARES METHOD, CURVE FITTING
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE