Pseudo-linear indentification: Optimal joint parameter and state estimation of linear stochastic MIMO systems

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Title: Pseudo-linear indentification: Optimal joint parameter and state estimation of linear stochastic MIMO systems
Author: Hopkins, Mark; VanLandingham, Hugh
Abstract: This paper presents a new method of joint parameter and stale estimation called pseudo-linear identification (PLID), extending a method given by Salut et.al. (I) to the more gencr31 case where the system inputs and output measurements arc corrupted by noise. PLID can be applied to linear, strictly proper, completely observable, completely controllable, discrete-time MIMO systems with known structure and unknown parameters, without assumptions about pole and zero locations. It is proved, under standard gaussian assumptions, that for lime- invariant systems PLI D is the optimal estimator (in the mean-square error sense) of the states and parameters conditioned on the input and output measurements; and. under a reasonable criterion for persistency of excitation, that the PLID parameter estimates converge a.e. to the true parameter values.
Record URI: http://hdl.handle.net/1850/10567
Date: 1988

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