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A note on sampling and parameter estimation in linear stochastic systems
Duncan, Tyrone E. Mandl, P. Pasik-Duncan, Bozenna
Duncan, Tyrone E.
Mandl, P.
Pasik-Duncan, Bozenna
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Abstract
Numerical differentiation formulas that yield consistent least squares parameter estimates from sampled observations of linear, time invariant higher order systems have been introduced previously by Duncan et al. The formulas given by Duncan ct ai. have the same limiting system of equations as in the continuous time case. The formula presented in this note can be characterized as preserving asymptotically a partial integration rule. It leads to limiting equations for the parameter estimates that are different from the continuous case, but they again imply consistency. The numerical differentiation formulas given here can be used for an arbitrary linear system, which is not the ease in the previous paper by Duncan et al.
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©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Date
1999-11
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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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00802928.pdf
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Keywords
Estimation, Linear stochastic systems, Numerical differentiation for stochastic systems, Sampling
Citation
Duncan, TE; Mandl, P; Pasik-Duncan, B. A note on sampling and parameter estimation in linear stochastic systems. IEEE TRANSACTIONS ON AUTOMATIC CONTROL. November 1999. 44(11) : 2120-2125