A Recursive Scheme for Gross Error Identification and Estimation

If combinations of leaks and measurement biases are considered, both the measurement model and the process constraints equations need to be modified. The formulation for the least squares problem is now [Pg.125]

we can use the Lagrangian approach to obtain estimates for mp, mb, e, and x. The estimates for mp and mb are obtained by solving the following system [Pg.125]

A RECURSIVE SCHEME FOR GROSS ERROR IDENTIFICATION AND ESTIMATION [Pg.125]

This section briefly discusses an approach that combines statistical tests with simultaneous gross error identification and estimation. The strategy is called SEGE (Simultaneous Estimation of Gross Error Method). It was proposed by Sanchez and Romagnoli (1994). [Pg.125]

Recall that, in the absence of gross errors, the measurement and linear constraint models are given by Eqs. (7.1) and (7.4), respectively. Furthermore, the solution of the least square estimation problem of x variables is [Pg.125]

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