## WMODEL - APMonitor Option

## Main.OptionWmodel History

Hide minor edits - Show changes to output

Changed line 13 from:

See also [[Main/OptionWmeas|WMEAS]],[[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]

to:

See also [[Main/OptionWmeas|WMEAS]], [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]

Changed lines 5-6 from:

%width=50px%Attach:cv.png

to:

%width=50px%Attach:cv.png [[Main/DbsVariable|Local Options]] | %width=30px%Attach:apm.png [[Main/DbsGlobal|Global Options]]

Changed line 13 from:

See also [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]

to:

See also [[Main/OptionWmeas|WMEAS]],[[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]

Added lines 12-13:

See also [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]

Added lines 1-11:

(:title WMODEL - APMonitor Option:)

(:keywords WMODEL, Optimization, Estimation, Option, Configure, Default, Description:)

(:description Objective function weight on model value:)

%width=50px%Attach:cv.png

Type: Floating Point, Input

Default Value: 2.0d0

Description: Objective function weight on model value

A weighting factor to penalize deviation of current model predictions from prior model predictions. This is used in estimation applications (APM.IMODE=2, 5, or 8) where the penalty from a prior model prediction is a βforgetting factorβ that approximates an infinite estimation horizon or favors prior predictions. The infinite estimation horizon approximation is especially useful for systems that have weakly observable or unobservable states. A higher WMODEL can also help to reduce the aggressiveness of the estimator in aligning with the measurements by balancing with a penalty against shifting too far from the prior predictions. The WMODEL value should never be equal to or larger than the WMEAS value for APM.EV_TYPE=1 (l1-norm). A WMODEL value higher than WMEAS will ignore measured values in favor of matching prior model predictions.

(:keywords WMODEL, Optimization, Estimation, Option, Configure, Default, Description:)

(:description Objective function weight on model value:)

%width=50px%Attach:cv.png

Type: Floating Point, Input

Default Value: 2.0d0

Description: Objective function weight on model value

A weighting factor to penalize deviation of current model predictions from prior model predictions. This is used in estimation applications (APM.IMODE=2, 5, or 8) where the penalty from a prior model prediction is a βforgetting factorβ that approximates an infinite estimation horizon or favors prior predictions. The infinite estimation horizon approximation is especially useful for systems that have weakly observable or unobservable states. A higher WMODEL can also help to reduce the aggressiveness of the estimator in aligning with the measurements by balancing with a penalty against shifting too far from the prior predictions. The WMODEL value should never be equal to or larger than the WMEAS value for APM.EV_TYPE=1 (l1-norm). A WMODEL value higher than WMEAS will ignore measured values in favor of matching prior model predictions.