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Control algorithm, minimum variance

Even starting off with poor initial controller parameter values, the self-tuning algorithm usually converges quite rapidly to a stable controller. After a certain amount of data has been collected one can test whether or not the assumed controller form is optimal (in the sense of the minimum variance) and then change it if necessary. [Pg.264]

The aim of the minimum-variance control algorithm is the minimization of the following performance index (Astrom and Wittenmark, 1995 Astrom and Wittenmark, 1990). [Pg.169]


See other pages where Control algorithm, minimum variance is mentioned: [Pg.478]    [Pg.479]    [Pg.482]    [Pg.73]    [Pg.261]    [Pg.263]    [Pg.73]    [Pg.559]    [Pg.948]    [Pg.233]    [Pg.272]    [Pg.953]    [Pg.739]    [Pg.751]    [Pg.151]    [Pg.300]   


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