WMODEL - APMonitor Option
Main.OptionWmodel History
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See also [[Main/OptionWmeas|WMEAS]],[[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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See also [[Main/OptionWmeas|WMEAS]], [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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See also [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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See also [[Main/OptionWmeas|WMEAS]],[[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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See also [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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(: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.