APM.EV_TYPE - APMonitor Option
Main.OptionApmEvType History
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%width=50px%Attach:apm.png [[Main/DbsGlobal|Global Options]] | %width=30px%Attach:fv.png %width=30px%Attach:mv.png %width=30px%Attach:sv.png %width=30px%Attach:cv.png[[Main/DbsVariable|Local Options]]
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See also [[https://apmonitor.com/do/index.php/Main/EstimatorObjective|Estimation Objective Tuning]]
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See also [[Main/OptionApmCvType|CV_TYPE]], [[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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Description: Estimated variable error model type: 1=linear, 2=squared, 3=approximate linear
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Description: Estimated variable error model type
1=linear error, abs(model-measured) with slacks
2=squared error, (model-measured)^2
3=approximate linear without slack variables
1=linear error, abs(model-measured) with slacks
2=squared error, (model-measured)^2
3=approximate linear without slack variables
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(:title APM.EV_TYPE - APMonitor Option:)
(:keywords APM.EV_TYPE, Optimization, Estimation, Option, Configure, Default, Description:)
(:description Estimated variable error model type: 1=linear, 2=squared, 3=approximate linear:)
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Type: Integer, Input
Default Value: 1
Description: Estimated variable error model type: 1=linear, 2=squared, 3=approximate linear
EV_TYPE applies a specific objective function. Linear is an l1-norm, or in other words the solver minimizes the sum of the absolute value of the difference between the CV and the set point. Squared is an l2-norm or sum squared error (SSE), or in other words the solver minimizes the sum of the squared difference between the CV and the set point. l1-norm can be useful when noise or measurement error is expected because it better rejects those. Option 3 is not typically used as an approximate absolute value function that uses a nonlinear function instead of slack variables.
(:keywords APM.EV_TYPE, Optimization, Estimation, Option, Configure, Default, Description:)
(:description Estimated variable error model type: 1=linear, 2=squared, 3=approximate linear:)
%width=50px%Attach:apm.png
Type: Integer, Input
Default Value: 1
Description: Estimated variable error model type: 1=linear, 2=squared, 3=approximate linear
EV_TYPE applies a specific objective function. Linear is an l1-norm, or in other words the solver minimizes the sum of the absolute value of the difference between the CV and the set point. Squared is an l2-norm or sum squared error (SSE), or in other words the solver minimizes the sum of the squared difference between the CV and the set point. l1-norm can be useful when noise or measurement error is expected because it better rejects those. Option 3 is not typically used as an approximate absolute value function that uses a nonlinear function instead of slack variables.